[r-cran-matchit] 43/45: New upstream version 3.0.1
Andreas Tille
tille at debian.org
Fri Oct 20 06:17:24 UTC 2017
This is an automated email from the git hooks/post-receive script.
tille pushed a commit to branch master
in repository r-cran-matchit.
commit 68703395fe8cb91c87f9fbfad033b64bacc596d6
Author: Andreas Tille <tille at debian.org>
Date: Fri Oct 20 08:11:04 2017 +0200
New upstream version 3.0.1
---
DESCRIPTION | 44 +-
MD5 | 77 +-
NAMESPACE | 45 +-
R/class_functions.R | 750 ++
R/discard.R | 13 +-
R/distance2GAM.R | 53 +-
R/distance2nnet.R | 10 +-
R/distance2rpart.R | 11 +-
R/help.matchit.R | 1 +
R/match.data.R | 1 +
R/matchit.R | 3 +-
R/matchit2cem.R | 7 +-
R/matchit2full.R | 5 +-
R/matchit2genetic.R | 9 +-
R/matchit2optimal.R | 11 +-
R/plot.matchit.R | 25 -
R/plot.matchit.subclass.R | 45 -
R/plot.summary.matchit.R | 42 -
R/print.matchit.R | 16 -
R/print.matchit.exact.R | 16 -
R/print.matchit.full.R | 17 -
R/print.matchit.subclass.R | 12 -
R/print.summary.matchit.R | 26 -
R/print.summary.matchit.exact.R | 11 -
R/print.summary.matchit.subclass.R | 20 -
R/summary.matchit.R | 82 -
R/summary.matchit.exact.R | 34 -
R/summary.matchit.full.R | 79 -
R/summary.matchit.subclass.R | 126 -
R/user.prompt.R | 1 +
README.md | 3 +
build/vignette.rds | Bin 0 -> 241 bytes
inst/doc/matchit.pdf | Bin 0 -> 281837 bytes
inst/doc/matchit.pdf.asis | 2 +
man/get_matches.Rd | 31 +
man/is.matchit.Rd | 19 +
man/lalonde.Rd | 5 +-
tests/testthat.R | 4 +
tests/testthat/test-get_matches.R | 289 +
vignettes/Makefile | 10 -
vignettes/asa.bst | 1505 ---
vignettes/balance.tex | 135 -
vignettes/dcolumn.sty | 91 -
vignettes/face_off.jpg | Bin 8958 -> 0 bytes
vignettes/faq.tex | 194 -
vignettes/gk.bib | 20380 -----------------------------------
vignettes/gkpubs.bib | 2259 ----
vignettes/graphics.R | 48 -
vignettes/html.sty | 360 -
vignettes/index.shtml | 72 -
vignettes/intro.tex | 84 -
vignettes/makematchH | 5 -
vignettes/matchit.pdf | Bin 600716 -> 0 bytes
vignettes/matchit.pdf.asis | 2 +
vignettes/matchit.tex | 209 -
vignettes/matchit2zelig.tex | 285 -
vignettes/matchitref.tex | 393 -
vignettes/mdataref.tex | 103 -
vignettes/notation.tex | 151 -
vignettes/overview.tex | 199 -
vignettes/plotref.tex | 105 -
vignettes/preprocess.tex | 233 -
vignettes/summaryref.tex | 127 -
63 files changed, 1253 insertions(+), 27642 deletions(-)
diff --git a/DESCRIPTION b/DESCRIPTION
index 262d6b4..d1694fb 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,24 +1,36 @@
Package: MatchIt
-Version: 2.4-21
-Date: 2013-06-26
-Title: MatchIt: Nonparametric Preprocessing for Parametric Casual
- Inference
-Author: Daniel Ho <daniel.e.ho at gmail.com>, Kosuke Imai
- <kimai at Princeton.Edu>, Gary King <king at harvard.edu>, Elizabeth
- Stuart <stuart at stat.harvard.edu>
+Version: 3.0.1
+Date: 2017-04-18
+Title: Nonparametric Preprocessing for Parametric Casual Inference
+Description: Selects matched samples of the original treated and
+ control groups with similar covariate distributions -- can be
+ used to match exactly on covariates, to match on propensity
+ scores, or perform a variety of other matching procedures. The
+ package also implements a series of recommendations offered in
+ Ho, Imai, King, and Stuart (2007) <DOI:10.1093/pan/mpl013>.
+Authors at R: c(
+ person("Daniel", "Ho", , "daniel.e.ho at gmail.com", c("aut")),
+ person("Kosuke", "Imai", , "kimai at Princeton.Edu", c("aut", "cre")),
+ person("Gary", "King", , "king at harvard.edu", c("aut")),
+ person("Elizabeth", "Stuart", , "stuart at stat.harvard.edu", c("aut")),
+ person("Alex", "Whitworth", , "whitworth.alex at gmail.com", c("ctb"))
+ )
Maintainer: Kosuke Imai <kimai at Princeton.Edu>
-Depends: R (>= 2.6), MASS
-Suggests: cem, optmatch, Matching, nnet, rpart, mgcv, WhatIf
-Description: MatchIt selects matched samples of the the original
- treated and control groups with similar covariate distributions
- -- can be used to match exactly on covariates, to match on
- propensity scores, or perform a variety of other matching
- procedures.
+Depends: R (>= 2.6)
+Imports: MASS, Matching, rgenoud
+Suggests: cem, nnet, optmatch, rpart, mgcv, WhatIf, R.rsp, testthat
+VignetteBuilder: R.rsp
LazyLoad: yes
LazyData: yes
License: GPL (>= 2)
URL: http://gking.harvard.edu/matchit
-Packaged: 2013-06-27 21:07:24 UTC; kimai
+RoxygenNote: 5.0.1
NeedsCompilation: no
+Packaged: 2017-04-18 12:13:20 UTC; kimai
+Author: Daniel Ho [aut],
+ Kosuke Imai [aut, cre],
+ Gary King [aut],
+ Elizabeth Stuart [aut],
+ Alex Whitworth [ctb]
Repository: CRAN
-Date/Publication: 2013-06-28 00:55:57
+Date/Publication: 2017-04-18 13:04:21 UTC
diff --git a/MD5 b/MD5
index 454df40..96a1535 100644
--- a/MD5
+++ b/MD5
@@ -1,44 +1,33 @@
-1d6ec647adf3b150e99efc85bc3fcefe *DESCRIPTION
-dc204a70f2b67992241ee0e5408ebd23 *NAMESPACE
-bc8a6a1ff969b14f81e943ddf3e4cb83 *R/discard.R
-105f86dfd4e75ca99cc84145f77724f4 *R/distance2GAM.R
+5ad5b77b983db990c01a5233fc09dfb7 *DESCRIPTION
+b30628ac0ee52d8b1610d133e572c902 *NAMESPACE
+9998c366a3c5c36d1d4ed1519a3bdaa8 *R/class_functions.R
+ed62025d3c0f97843134e919fe3534d9 *R/discard.R
+7c0120871315fade6af6cee738422bf1 *R/distance2GAM.R
7609f0509313c85eebe66fe1493f1389 *R/distance2glm.R
144da2b6b682f5c41a9482dd487b53b9 *R/distance2mahalanobis.R
-ce14dad890ce5071548cbde4d3b7aee4 *R/distance2nnet.R
-931e8cd4c0ae35bd58e396468ea2b340 *R/distance2rpart.R
+a43c16d86d85965e99ccd02f201e305e *R/distance2nnet.R
+f016cd083061d48afc0e964838fcc0bf *R/distance2rpart.R
5f580ff3918496a1a445853fdc6b8fe0 *R/eqqplot.R
-ebea74fac3a3c58bebf5271051968aec *R/help.matchit.R
+92f1489efe0a6a454954434751ce438b *R/help.matchit.R
52e4ed5c0327fbcc2b668b3f1af53a84 *R/hist.pscore.R
3c36d8f77d3aec21fca511bd1eef4f16 *R/jitter.pscore.R
-00a4040ed1dd52f712af0d0b30b52db5 *R/match.data.R
+37b950f95aaa46c2ad5afbb1c586948c *R/match.data.R
6cbef71c72b30938dd82993e06398ca3 *R/match.qoi.R
-1ccd1a4b57991395229239054b9b9a3e *R/matchit.R
+cf940b61b98c0483b2b540d80fc19853 *R/matchit.R
4b04e5ff6fc50b37773b4cb1aecbf2cf *R/matchit.qqplot.R
-cd4e84995fff9f7b96662135b79bf786 *R/matchit2cem.R
+5178cebc57f2f2a2db69c30693b51372 *R/matchit2cem.R
21a14b702e7d501cdf4161af256b2e7c *R/matchit2exact.R
-07fd880f983711d3b2e4dd7be94cc73c *R/matchit2full.R
-914addf1d6c24a82fbc36d838ddd012e *R/matchit2genetic.R
+b04b32355fd52db047e6b3b0638e5952 *R/matchit2full.R
+5c0028a2107aba0f7c71c80add98b1d9 *R/matchit2genetic.R
aa55850e4a029db31a1c57328d5a785b *R/matchit2nearest.R
-faff750b898c0e464fd0bb0527fd2ac6 *R/matchit2optimal.R
+e610d71c6f932f36037766b847297ab9 *R/matchit2optimal.R
8991d0cf380be259b3f76d8d12de7378 *R/matchit2subclass.R
-0aea9be3857a1615224574d3bb070c17 *R/plot.matchit.R
-42df7223665e64039685c04df289ec02 *R/plot.matchit.subclass.R
-56f6332707c706c90031deba83c11997 *R/plot.summary.matchit.R
-a37cc8fc172ab18faabc3b51e279e6f7 *R/print.matchit.R
-f33bb649fdd5f26dd8612daa7b647cb9 *R/print.matchit.exact.R
-62f401588a49e15e9d1896f480f86b26 *R/print.matchit.full.R
-ea652f0bcd9ec680649bc663642737ee *R/print.matchit.subclass.R
-8bf365dfaf6270ea240a9814ded6ed08 *R/print.summary.matchit.R
-74d977ab1c54520426a26f7de57eb7a3 *R/print.summary.matchit.exact.R
-350d6d6bad592afa2e6b8daa53892e52 *R/print.summary.matchit.subclass.R
1dd4a4ccfab350865e0d5e218c156a8a *R/qqsum.R
-d61583cd5d64abb1c548dc7ca0ce6abf *R/summary.matchit.R
-abd44066b7992377acccebb825bb9fb2 *R/summary.matchit.exact.R
-b8eb4fe3ac4a5aa02a3f03c5fcf1cbc0 *R/summary.matchit.full.R
-0e20487a85c99769f8b0e63368091c35 *R/summary.matchit.subclass.R
-950b76a8b5b742dc4714ce93e730ff5f *R/user.prompt.R
+a5e34bb95ca36b69d0d3e65d8eced694 *R/user.prompt.R
dc1fdc9ceaf5b35d0a69cc189db06dc2 *R/weights.matrix.R
5d82fa6c1ae051325128757a29e38c55 *R/weights.subclass.R
+8e5a3e58c45c1ebacfeae12811807976 *README.md
+329e56593217fa0c9048b18f6dce2922 *build/vignette.rds
a1a7a516af5ac0a8d1967cb29eb4acfe *data/lalonde.tab.gz
870d0ee00f3fd621950dc7cfe268317a *demo/00Index
da045e6883d634901d49484ab0dfcb1d *demo/analysis.R
@@ -51,31 +40,15 @@ c959726a30ddc8b1883717eedbc7c912 *demo/nearest.R
878dbcbd1c485d1b3e71a72f73960385 *demo/optimal.R
e08c2401c4a03d9e5f37456be103572a *demo/subclass.R
3eda425777172d9aaa9d907061df3387 *inst/CITATION
+2f9bde7d816114183d114957cf0fbb61 *inst/doc/matchit.pdf
+45b7c211157672e0d15c81c74de32cfe *inst/doc/matchit.pdf.asis
+d4c5f142981d7eba4e9883acd24d4333 *man/get_matches.Rd
6312a97d096669571c74667ef6cc078a *man/help.matchit.Rd
-2406dec35f1350b6ddbe61a3e3a2e6f7 *man/lalonde.Rd
+385bd1702bc302dc9a75b84ff85f58bc *man/is.matchit.Rd
+0358b2f82d3ddfa8a642b726b0c34755 *man/lalonde.Rd
d3b0d22dad0e64fcf5b84f3303f7bc7a *man/match.data.Rd
605af5ede3b2290c6233be639f85cb58 *man/matchit.Rd
4cc2194b9b06d3765105272f7618dff5 *man/user.prompt.Rd
-74af268b63206f2e4d8f5a2fb2524294 *vignettes/Makefile
-c3c7f26c2e84a1eecfb3ec0c0b37159d *vignettes/asa.bst
-f87006e9491e7a4177175b7520a8910b *vignettes/balance.tex
-d816267de5c98f628c5f66e3ad65f1f1 *vignettes/dcolumn.sty
-a3707e9f4be0b8ab99cc8a31bf591a90 *vignettes/face_off.jpg
-ac28f0dbf93b6d593a6b3719497ac133 *vignettes/faq.tex
-20775eb895fffe614893f4f1b2ae19e5 *vignettes/gk.bib
-a35da60f3f139a9a7cd6749353eb430f *vignettes/gkpubs.bib
-1d64d9435ec019005bcd4768cd64d5bb *vignettes/graphics.R
-d66fa8f1c8db29c2d11842496bf29064 *vignettes/html.sty
-bb062f81aba5fc15b3dd7b8b95c6f950 *vignettes/index.shtml
-d3d0a275f38ef9a70cc29ea6891ab5f6 *vignettes/intro.tex
-fe44cc2288769a96718c4a3377af2e6a *vignettes/makematchH
-27ebdf9a173b6210592f5ef7ff5518b9 *vignettes/matchit.pdf
-4cd51e387b66c3183da2cdd8f1eb309c *vignettes/matchit.tex
-a627a20fb6aab7beddaedf6d317ab080 *vignettes/matchit2zelig.tex
-d1e3ba947a8ba3d434096bd4677e1eba *vignettes/matchitref.tex
-f50b58f9f778170f752e6924022993b2 *vignettes/mdataref.tex
-9301a74af38f9e7259e75be6594541d3 *vignettes/notation.tex
-b54051c8d51f38cf128c09e50841081a *vignettes/overview.tex
-77e2abd6da40f9154ee2683e4f280b41 *vignettes/plotref.tex
-662649fb68f014608424bc21b49237f6 *vignettes/preprocess.tex
-f6e303070a59b15096f3bcda0e871258 *vignettes/summaryref.tex
+4077dcfde39f1437a7af9482cf787086 *tests/testthat.R
+ca1cec28cd1042112fca6ec3c413e549 *tests/testthat/test-get_matches.R
+45b7c211157672e0d15c81c74de32cfe *vignettes/matchit.pdf.asis
diff --git a/NAMESPACE b/NAMESPACE
index d6f4433..b0dbb90 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -1,20 +1,27 @@
-import(MASS)
-export(matchit,
- help.matchit,
- match.data,
- user.prompt)
-
-S3method(print, matchit)
-S3method(print, matchit.exact)
-S3method(print, matchit.subclass)
-S3method(print, summary.matchit)
-S3method(print, summary.matchit.exact)
-S3method(print, summary.matchit.subclass)
-S3method(plot, matchit)
-S3method(plot, summary.matchit)
-S3method(plot, matchit.subclass)
-S3method(summary, matchit)
-S3method(summary, matchit.exact)
-S3method(summary, matchit.subclass)
-S3method(summary, matchit.full)
+# Generated by roxygen2: do not edit by hand
+S3method(get_matches,matchit)
+S3method(plot,matchit)
+S3method(plot,matchit.subclass)
+S3method(plot,summary.matchit)
+S3method(print,matchit)
+S3method(print,matchit.exact)
+S3method(print,matchit.full)
+S3method(print,matchit.subclass)
+S3method(print,summary.matchit)
+S3method(print,summary.matchit.exact)
+S3method(print,summary.matchit.subclass)
+S3method(summary,matchit)
+S3method(summary,matchit.exact)
+S3method(summary,matchit.full)
+S3method(summary,matchit.subclass)
+export(get_matches)
+export(help.matchit)
+export(is.matchit)
+export(match.data)
+export(matchit)
+export(user.prompt)
+import(MASS)
+import(graphics)
+import(stats)
+import(utils)
diff --git a/R/class_functions.R b/R/class_functions.R
new file mode 100644
index 0000000..8f6e03a
--- /dev/null
+++ b/R/class_functions.R
@@ -0,0 +1,750 @@
+
+#' @import MASS
+#' @import stats
+#' @import utils
+#' @import graphics
+
+in_frame <- function(df, col) {
+ exists(col, envir= as.environment(df))
+}
+
+int_rownames <- function(mat) {
+ options(warn= -1)
+ rn <- as.integer(rownames(mat))
+ options(warn= 0)
+ if (any(is.na(rn))) return(FALSE)
+ else return(TRUE)
+}
+
+#----------------------------------------------------------
+### Inheritance
+#----------------------------------------------------------
+
+#' @title Checks matchit Class
+#' @description Function that checks if the target object is a \code{matchit} object.
+#' @param object any R object
+#' @return Returns \code{TRUE} if its argument has class "matchit" among its classes and
+#' \code{FALSE} otherwise.
+#' @export
+is.matchit <- function(object) {
+ inherits(object, "matchit")
+}
+
+
+#----------------------------------------------------------
+### GET MATCHES
+#----------------------------------------------------------
+
+#' @title Get matches from matchit object
+#' @description Get the resulting matches from a \code{matchit} model object. This function allows the
+#' user to extract the matches from the original dataset used in model building or from a new dataset
+#' that has a matching set of key column(s) (\code{id_cols}).
+#' @param object The \code{'matchit'} class model object
+#' @param model_frame The \code{'data.frame'} class object used in creation of \code{object}.
+#' @param id_cols A string indicating the ID for the datset used in the call to \code{\link{matchit}}.
+#' This can be used in combination with \code{newdata} to return the base dataset. Defaults to
+#' \code{NULL}.
+#' @param newdata A new \code{data.frame} object to extract matched observations from. Used in
+#' conjunction with \code{id_cols}. Defaults to \code{NULL}.
+#' @return If \code{newdata} is \code{NULL}, a subset of \code{model_frame} containing the rows
+#' corresponding to the matched treatement and control observations with weights appended. If
+#' \code{newdata} is not \code{NULL}, an equivalent subset of \code{newdata} is returned.
+#' @export
+get_matches <- function(object, model_frame, id_cols= NULL, newdata= NULL) {
+ UseMethod("get_matches", object)
+}
+
+
+#' @export
+get_matches.matchit <- function(object, model_frame, id_cols= NULL, newdata= NULL) {
+ # 00. error checking
+ if (!is.matchit(object)) stop("object must be a class 'matchit' object.")
+ if (!is.data.frame(model_frame)) stop("model_frame must be a data.frame")
+ if (nrow(model_frame) != nrow(object$X))
+ stop("model_frame must have the same number of rows as the data used in the call to 'matchit'.")
+ if ( (!is.null(id_cols) & is.null(newdata)) | (is.null(id_cols) & !is.null(newdata)) ) {
+ stop("For identity returns, both id_cols and newdata must be supplied.")
+ }
+ if (!is.null(id_cols) & !is.null(newdata)) {
+ if (!is.character(id_cols)) stop("id_cols must be a character vector.")
+ if (!all(sapply(id_cols, in_frame, df= model_frame)))
+ stop("all values in id_cols must exist in model_frame")
+ if (!all(sapply(id_cols, in_frame, df= newdata)))
+ stop("all values in id_cols must exist in newdata")
+ }
+
+ # 01. preliminaries
+ if ( any(grepl(pattern= "replace", x= names(object$call))) ) {
+ idx_call_replace <- which(names(object$call) == "replace")
+ } else {
+ idx_call_replace <- -1L
+ }
+ use_subclass_matching <- base::grepl(x = object$call[4],
+ pattern= paste(c("exact", "full", "subclass", "cem"), collapse= "|"),
+ ignore.case= TRUE)
+ # [deprecated] use_genetic_matching <- base::grepl(x = object$call[4], pattern= "genetic", ignore.case= TRUE)
+ use_newdata <- ifelse(is.null(newdata), FALSE, TRUE)
+ has_int_rownames <- int_rownames(model_frame)
+
+ # 02. extract pairs, either exact matching or otherwise
+ if (use_subclass_matching) {
+ if (has_int_rownames) {
+ row_idx <- as.integer(names(object$subclass)[which(!is.na(object$subclass))])
+ match_wts <- object$weights[which(!is.na(object$subclass))]
+ model_subset <- data.frame(model_frame[row_idx, ], weight= match_wts)
+ } else {
+ row_idx <- names(object$subclass)[which(!is.na(object$subclass))]
+ match_wts <- object$weights[which(!is.na(object$subclass))]
+ model_subset <- data.frame(model_frame[which(rownames(model_frame) %in% row_idx), ],
+ weight= match_wts)
+ }
+ } else {
+ model_subset <- get_matches_non_subclass(object= object, model_frame= model_frame,
+ has_int_rownames= has_int_rownames,
+ idx_call_replace= idx_call_replace)
+ }
+
+ # 03. return
+ if (!use_newdata) {
+ return(model_subset)
+ } else { # using newdata via id_cols
+ newdata <- base::as.data.frame(newdata) # in case of data.table
+ unique_ids <- base::unique(x= model_subset[, c(id_cols, "weight")])
+ # use of all == FALSE for two cases:
+ # a) newdata contains additional IDs not in the matching data -- most common
+ # b) if model_subset contains IDs that newdata does not have -- less common
+ return(merge(newdata, unique_ids, by= id_cols, all.x=FALSE, all.y=FALSE))
+ }
+}
+
+get_matches_non_subclass <- function(object, model_frame, has_int_rownames, use_genetic_matching,
+ idx_call_replace) {
+ ## get match weights
+ n_matches <- ncol(object$match.matrix)
+ # get control observations that have matches and their frequency (ie weight)
+ control_units <- object$match.matrix
+ attr(control_units, "dim") <- NULL
+ control_units <- control_units[!is.na(control_units)]
+
+ control_wts <- table(control_units); class(control_wts) <- "vector"
+ control_wts <- data.frame(ob= names(control_wts), weight= control_wts / n_matches,
+ stringsAsFactors= FALSE)
+
+ if (has_int_rownames) {
+ treated_obs <- data.frame(model_frame[as.integer(rownames(object$match.matrix)), ], weight= 1)
+ control_obs <- data.frame(model_frame[as.integer(control_wts$ob), ],
+ weight= control_wts$weight)
+ } else {
+ treated_obs <- data.frame(
+ model_frame[which(rownames(model_frame) %in% rownames(object$match.matrix)), ],
+ weight= 1)
+
+ model_frame$rownames <- rownames(model_frame)
+ control_obs <- merge(model_frame, control_wts, by.x= "rownames", by.y= "ob", all= FALSE)
+ rownames(control_obs) <- control_obs$rownames
+ control_obs$rownames <- NULL
+ control_obs$ob <- NULL
+ }
+
+ model_subset <- do.call("rbind", list(control_obs, treated_obs))
+ return(model_subset)
+}
+
+#----------------------------------------------------------
+### PLOT METHODS
+#----------------------------------------------------------
+
+# Need to account for weights -- how do we do qq plots with weights
+#' @export
+plot.matchit <- function(x, discrete.cutoff=5, type="QQ",
+ numdraws=5000, interactive = T, which.xs =
+ NULL, ...){
+ if ("matchit.exact" %in% class(x)){
+ stop("Not appropriate for exact matching. No plots generated.")
+ }
+ if(type=="QQ"){
+ matchit.qqplot(x=x,discrete.cutoff=discrete.cutoff,
+ numdraws=numdraws, interactive=interactive,
+ which.xs = which.xs, ...)
+ } else if(type=="jitter"){
+ if("matchit.mahalanobis" %in% class(x)){
+ stop("Not appropriate for pure Mahalanobis matching. No plots generated.")
+ }
+ jitter.pscore(x, interactive=interactive,...)
+ } else if(type=="hist"){
+ if("matchit.mahalanobis" %in% class(x)){
+ stop("Not appropriate for pure Mahalanobis matching. No plots generated.")
+ }
+ hist.pscore(x,...)
+ } else {
+ stop("Invalid type")
+ }
+}
+
+#' @export
+plot.matchit.subclass <- function(x, discrete.cutoff=5,
+ type="QQ", interactive = T,
+ subclass = NULL, which.xs=NULL,...){
+ choice.menu <- function(choices,question)
+ {
+ k <- length(choices)-1
+ Choices <- data.frame(choices)
+ row.names(Choices) <- 0:k
+ names(Choices) <- "Choices"
+ print.data.frame(Choices,right=FALSE)
+ ans <- readline(question)
+ while(!ans%in%c(0:k))
+ {
+ print("Not valid -- please pick one of the choices")
+ print.data.frame(Choices,right=FALSE)
+ ans <- readline(question)
+ }
+ return(ans)
+ }
+ if(type=="QQ"){
+ if(interactive){
+ choices <- c("No",paste("Yes : Subclass ", 1:max(x$subclass,na.rm=T)))
+ question <- "Would you like to see quantile-quantile plots of any subclasses?"
+ ans <- -1
+ while(ans!=0)
+ {
+ ans <- as.numeric(choice.menu(choices,question))
+ if(ans!=0)
+ {
+ matchit.qqplot(x,discrete.cutoff,which.subclass=ans,
+ interactive = interactive, which.xs=which.xs,...)
+ }
+ }
+ } else {
+ matchit.qqplot(x,discrete.cutoff,which.subclass=subclass,
+ interactive=interactive, which.xs=which.xs,...)
+ }
+ } else if(type=="jitter"){
+ jitter.pscore(x, interactive=interactive,...)
+ } else if(type=="hist"){
+ hist.pscore(x,...)
+ } else {
+ stop("Invalid type")
+ }
+}
+
+
+#' @export
+plot.summary.matchit <- function(x, interactive = TRUE, ...) {
+ if ("matchit.exact" %in% class(x)){
+ stop("Not appropriate for exact matching. No plots generated.")
+ }
+
+ if (!"Std. Mean Diff."%in%names(x$sum.all)){
+ stop(paste("Not appropriate for unstandardized summary. Run summary() with the ",
+ "standardize=TRUE option, and then plot."))
+ }
+
+ sd.pre <- abs(x$sum.all$"Std. Mean Diff.")
+ sd.post <- abs(x$sum.matched$"Std. Mean Diff.")
+
+ if (!is.null(x$q.table)) sd.post <- abs(x$sum.subclass$"Std. Mean Diff")
+
+ ases.dat <- data.frame(es.unw = sd.pre, es.w = sd.post)
+ par(mfrow=c(1,1))
+ plot(c(0.85, 2.15), c(0, min(3, max(unlist(ases.dat[,
+ 1:2]), na.rm = TRUE))), type = "n", xaxt = "n",
+ ylab = "Absolute Standardized Diff in Means",
+ xlab = "", main = "")
+ abline(h = c(0.2, 0.4, 0.6, 0.8, 1.0))
+ axis(side = 1, at = 1:2, labels = c("All Data", "Matched Data"))
+ for (i in 1:nrow(ases.dat)) {
+ points(1:2, abs(ases.dat[i, c("es.unw", "es.w")]),
+ type = "b", col = "grey", pch=19)
+ }
+ temp1 <- ases.dat[abs(ases.dat$es.unw) < abs(ases.dat$es.w),]
+ for (i in 1:nrow(temp1)) {
+ points(1:2, abs(temp1[i, c("es.unw", "es.w")]), type = "b",
+ col = "black", lwd = 2, pch=19)
+ }
+ if (max(ases.dat$es.w, na.rm = TRUE) > 3)
+ mtext(text = "Some standardized diffs in means > 3 after matching!", side = 3,
+ col = "red")
+
+ if(interactive==TRUE) {
+ print("To identify the variables, use first mouse button; to stop, use second.")
+ identify(rep(1, length(sd.pre)),sd.pre,rownames(x$sum.all),atpen=T)
+ identify(rep(2, length(sd.post)),sd.post,rownames(x$sum.all),atpen=T)
+ }
+}
+
+#----------------------------------------------------------
+### PRINT METHODS
+#----------------------------------------------------------
+
+#' @export
+print.matchit <- function(x, digits = getOption("digits"), ...){
+ cat("\nCall: ", deparse(x$call), sep="\n")
+ cat("\nSample sizes:\n")
+
+ #if(any(x$weights>0))
+ # nn <- rbind(table(x$treat),
+ # table(x$weights>0, x$treat),
+ # c(0,0))
+ #else
+ # nn <- rbind(table(x$treat),
+ # table(x$weights>0,x$treat)[2:1,])
+
+ print.table(x$nn, ...)
+ invisible(x)
+ cat("\n")
+}
+
+#' @export
+print.matchit.exact <- function(x, digits = getOption("digits"), ...){
+ cat("\nCall: ", deparse(x$call), sep = "\n")
+ cat("\nExact Subclasses: ", max(x$subclass, na.rm=T),"\n",sep="")
+ cat("\nSample sizes:\n")
+ ntab <- table(factor(!is.na(x$subclass),
+ levels=c("TRUE","FALSE")),
+ x$treat)
+ nn <- rbind(table(x$treat),
+ ntab[c("TRUE","FALSE"),])
+ dimnames(nn) <- list(c("All","Matched","Unmatched"),
+ c("Control","Treated"))
+ print.table(nn, ...)
+ invisible(x)
+ cat("\n")
+}
+
+#' @export
+print.matchit.full <- function(x, digits = getOption("digits"), ...){
+ cat("\nCall: ", deparse(x$call), sep = "\n")
+ cat("\nSample sizes:\n")
+
+ if (any(x$weights>0))
+ nn <- rbind(table(x$treat),
+ table(x$weights>0, x$treat),
+ c(0,0))
+ else
+ nn <- rbind(table(x$treat),
+ table(x$weights>0,x$treat)[2:1,])
+ dimnames(nn) <- list(c("All","Matched","Discarded"),
+ c("Control","Treated"))
+ print.table(nn, ...)
+ invisible(x)
+ cat("\n")
+}
+
+#' @export
+print.matchit.subclass <- function(x, digits = getOption("digits"), ...){
+ cat("\nCall: ", deparse(x$call), sep = "\n")
+ cat("\nSample sizes by subclasses:\n\n")
+ nsub <- table(x$subclass,x$treat)
+ nn <- rbind(table(x$treat),nsub)
+ dimnames(nn) <-
+ list(c("All",paste("Subclass",dimnames(nsub)[[1]])),
+ c("Control","Treated"))
+ print.table(nn, ...)
+ invisible(x)
+ cat("\n")
+}
+
+#' @export
+print.summary.matchit.exact <- function(x, digits = max(3,
+ getOption("digits") - 3),
+ ...){
+ cat("\nCall:", deparse(x$call), sep = "\n")
+ cat("\nSample sizes:\n")
+ print.table(x$nn,digits=digits)
+ cat("\nMatched sample sizes by subclass:\n")
+ print.data.frame(x$q.table, digits = digits)
+ cat("\n")
+ invisible(x)
+}
+
+#' @export
+print.summary.matchit <- function(x, digits = max(3,
+ getOption("digits") - 3), ...){
+
+ sum.all <- x$sum.all
+ sum.matched <- x$sum.matched
+ q.table <- x$q.table
+ xn <- x$nn
+ cat("\nCall:", deparse(x$call), sep = "\n")
+ cat("\nSummary of balance for all data:\n")
+ print.data.frame(round(sum.all,digits))
+ cat("\n")
+
+ xs1 <- sum.matched
+ cc <- row.names(sum.all)
+ if(!is.null(x$sum.matched) | identical(eval(x$call$method),"All"))
+ {
+ cat("\nSummary of balance for matched data:\n")
+ print.data.frame(round(xs1,digits))
+ cat("\nPercent Balance Improvement:\n")
+ print.data.frame(round(x$reduction,digits))
+ cat("\nSample sizes:\n")
+ print.table(xn, digits=digits)
+ cat("\n")
+ }
+ invisible(x)
+}
+
+#' @export
+print.summary.matchit.subclass <- function(x, digits = max(3,
+ getOption("digits") -
+ 3), ...){
+ sum.all <- x$sum.all
+ sum.matched <- x$sum.matched
+ q.table <- x$q.table
+ cat("\nCall:", deparse(x$call), sep = "\n")
+ cat("Summary of balance for all data:\n")
+ print.data.frame(round(sum.all,digits))
+ cat("\n")
+ cat("\nSummary of balance by subclasses:\n")
+ print.table(round(q.table, digits))
+ cat("\nSample sizes by subclasses:\n")
+ print.data.frame(x$qn, digits = digits)
+ cat("\nSummary of balance across subclasses\n")
+ print.data.frame(round(x$sum.subclass, digits))
+ cat("\nPercent Balance Improvement:\n")
+ print.data.frame(round(x$reduction,digits))
+ cat("\n")
+}
+
+
+#----------------------------------------------------------
+### SUMMARY METHODS
+#----------------------------------------------------------
+
+#' @export
+summary.matchit <- function(object, interactions = FALSE,
+ addlvariables = NULL, standardize = FALSE,
+ ...) {
+
+ X <- object$X
+ ## Fix X matrix so that it doesn't have any factors
+ varnames <- colnames(X)
+ for(var in varnames) {
+ if(is.factor(X[,var])) {
+ tempX <- X[,!colnames(X)%in%c(var)]
+ form<-formula(substitute(~dummy-1,list(dummy=as.name(var))))
+ X <- cbind(tempX, model.matrix(form, X))
+ }
+ }
+
+ ## No distance output for pure Mahalanobis
+ if("matchit.mahalanobis"%in%class(object)){
+ XX <- X
+ } else{
+ XX <- cbind(distance=object$distance,X)
+ }
+ if (!is.null(addlvariables)) XX <- cbind(XX, addlvariables)
+
+ treat <- object$treat
+ weights <- object$weights
+ nam <- dimnames(XX)[[2]]
+ dupnam <- duplicated(nam)
+ if(sum(dupnam)>0){
+ nam[dupnam] <- paste(nam[dupnam],".1",sep="")
+ }
+ kk <- ncol(XX)
+
+ ## Summary Stats
+ aa <- apply(XX,2,qoi,tt=treat,ww=weights,standardize=standardize,std=T)
+ sum.all <- as.data.frame(matrix(0,kk,7))
+ sum.matched <- as.data.frame(matrix(0,kk,7))
+ row.names(sum.all) <- row.names(sum.matched) <- nam
+ names(sum.all) <- names(sum.matched) <- names(aa[[1]])
+ sum.all.int <- sum.matched.int <- NULL
+ for(i in 1:kk){
+ sum.all[i,] <- aa[[i]][1,]
+ sum.matched[i,] <- aa[[i]][2,]
+ if(interactions){
+ for(j in i:kk){
+ x2 <- XX[,i]*as.matrix(XX[,j])
+ jqoi <- qoi(x2,tt=treat,ww=weights,standardize=standardize,std=T)
+ sum.all.int <- rbind(sum.all.int,jqoi[1,])
+ sum.matched.int <- rbind(sum.matched.int,jqoi[2,])
+ row.names(sum.all.int)[nrow(sum.all.int)] <-
+ row.names(sum.matched.int)[nrow(sum.matched.int)] <-
+ paste(nam[i],nam[j],sep="x")
+ }
+ }
+ }
+ xn <- aa[[1]]$xn
+ sum.all <- rbind(sum.all,sum.all.int)
+ sum.matched <- rbind(sum.matched,sum.matched.int)
+
+ ## Imbalance Reduction
+ stat0 <- abs(cbind(sum.all[,2]-sum.all[,1],
+ sum.all[,5:7]))
+ stat1 <- abs(cbind(sum.matched[,2]-sum.matched[,1],
+ sum.matched[,5:7]))
+ reduction <- as.data.frame(100*(stat0-stat1)/stat0)
+ if(sum(stat0==0 & stat1==0, na.rm=T)>0){
+ reduction[stat0==0 & stat1==0] <- 0
+ }
+ if(sum(stat0==0 & stat1>0,na.rm=T)>0){
+ reduction[stat0==0 & stat1>0] <- -Inf
+ }
+ if (standardize)
+ names(reduction) <- c("Std. Mean Diff.", "eCDF Med","eCDF Mean",
+ "eCDF Max")
+ else
+ names(reduction) <- c("Mean Diff.", "eQQ Med","eQQ Mean", "eQQ Max")
+
+ ## output
+ res <- list(call=object$call, nn = object$nn, sum.all = sum.all,
+ sum.matched = sum.matched, reduction = reduction)
+ class(res) <- "summary.matchit"
+ return(res)
+}
+
+
+#' @export
+summary.matchit.exact <- function(object, covariates = FALSE, ...) {
+ XX <- object$X
+ treat <- object$treat
+ qbins <- max(object$subclass,na.rm=TRUE)
+ if(!covariates){
+ q.table <- as.data.frame(matrix(0,qbins,3))
+ names(q.table) <- c("Treated","Control","Total")
+ for(i in 1:qbins){
+ qi <- object$subclass==i
+ q.table[i,] <- c(sum(treat[qi]==1, na.rm=T), sum(treat[qi]==0, na.rm=T),
+ length(treat[qi & !is.na(qi)]))
+ }
+ } else {
+ kk <- ncol(XX)
+ q.table <- as.data.frame(matrix(0,qbins,kk+3))
+ names(q.table) <- c("Treated","Control","Total",dimnames(XX)[[2]])
+ for(i in 1:qbins){
+ qi <- object$subclass==i & !is.na(object$subclass==i)
+ q.table[i,] <- c(sum(treat[qi]==1, na.rm=T), sum(treat[qi]==0, na.rm=T),
+ length(treat[qi & !is.na(qi)]),as.numeric(XX[qi,,drop=F][1,]))
+ }
+ }
+ ntab <- table(factor(!is.na(object$subclass),
+ levels=c("TRUE","FALSE")), treat)
+ nn <- rbind(table(treat),
+ ntab[c("TRUE","FALSE"),])
+ dimnames(nn) <- list(c("All","Matched","Discarded"),
+ c("Control","Treated"))
+ ## output
+ res <- list(q.table = q.table, nn = nn, subclass = object$subclass,
+ treat = object$treat, call = object$call)
+ class(res) <- c("summary.matchit.exact", "summary.matchit")
+ return(res)
+}
+
+
+#' @export
+summary.matchit.full <- function(object, interactions = FALSE,
+ addlvariables = NULL, numdraws =
+ 5000, standardize = FALSE,
+ ...) {
+
+ XX <- cbind(distance=object$distance,object$X)
+ if (!is.null(addlvariables)) XX <- cbind(XX, addlvariables)
+
+ treat <- object$treat
+ weights <- object$weights
+ nam <- dimnames(XX)[[2]]
+ kk <- ncol(XX)
+
+ ## Get samples of T and C units to send to qqplot
+ t.plot <- sample(names(treat)[treat==1], numdraws/2, replace=TRUE, prob=weights[treat==1])
+ c.plot <- sample(names(treat)[treat==0], numdraws/2, replace=TRUE, prob=weights[treat==0])
+
+ ## Summary Stats
+ aa <- apply(XX,2,qoi,tt=treat,ww=weights, t.plot=t.plot,
+ c.plot=c.plot, standardize=standardize)
+ sum.all <- as.data.frame(matrix(0,kk,6))
+ sum.matched <- as.data.frame(matrix(0,kk,6))
+ row.names(sum.all) <- row.names(sum.matched) <- nam
+ names(sum.all) <- names(sum.matched) <- names(aa[[1]])
+ sum.all.int <- sum.matched.int <- NULL
+ for(i in 1:kk){
+ sum.all[i,] <- aa[[i]][1,]
+ sum.matched[i,] <- aa[[i]][2,]
+ if(interactions){
+ for(j in i:kk){
+ x2 <- XX[,i]*as.matrix(XX[,j])
+ names(x2) <- names(XX[,1])
+ jqoi <- qoi(x2,tt=treat,ww=weights, t.plot=t.plot,
+ c.plot=c.plot, standardize=standardize)
+ sum.all.int <- rbind(sum.all.int,jqoi[1,])
+ sum.matched.int <- rbind(sum.matched.int,jqoi[2,])
+ row.names(sum.all.int)[nrow(sum.all.int)] <-
+ row.names(sum.matched.int)[nrow(sum.matched.int)] <-
+ paste(nam[i],nam[j],sep="x")
+ }
+ }
+ }
+ xn <- aa[[1]]$xn
+ sum.all <- rbind(sum.all,sum.all.int)
+ sum.matched <- rbind(sum.matched,sum.matched.int)
+
+ ## Imbalance Reduction
+ stat0 <- abs(cbind(sum.all[,2]-sum.all[,1],
+ sum.all[,4:6]))
+ stat1 <- abs(cbind(sum.matched[,2]-sum.matched[,1],
+ sum.matched[,4:6]))
+ reduction <- as.data.frame(100*(stat0-stat1)/stat0)
+ if(sum(stat0==0 & stat1==0, na.rm=T)>0){
+ reduction[stat0==0 & stat1==0] <- 0
+ }
+ if(sum(stat0==0 & stat1>0,na.rm=T)>0){
+ reduction[stat0==0 & stat1>0] <- -Inf
+ }
+ if (standardize)
+ names(reduction) <- c("Std. Mean Diff.", "eCDF Med","eCDF Mean", "eCDF Max")
+ else
+ names(reduction) <- c("Mean Diff.", "eQQ Med","eQQ Mean", "eQQ Max")
+
+ ## Sample sizes
+ nn <- matrix(0, ncol=2, nrow=4)
+ nn[1,] <- c(sum(object$treat==0), sum(object$treat==1))
+ nn[2,] <- c(sum(object$treat==0 & object$weights>0), sum(object$treat==1 & object$weights>0))
+ nn[3,] <- c(sum(object$treat==0 & object$weights==0 & object$discarded==0),
+ sum(object$treat==1 & object$weights==0 & object$discarded==0))
+ nn[4,] <- c(sum(object$treat==0 & object$weights==0 & object$discarded==1),
+ sum(object$treat==1 & object$weights==0 & object$discarded==1))
+
+ dimnames(nn) <- list(c("All","Matched","Unmatched","Discarded"),
+ c("Control","Treated"))
+
+ ## output
+ res <- list(call=object$call, nn = nn, sum.all = sum.all, sum.matched = sum.matched,
+ reduction = reduction)
+ class(res) <- c("summary.matchit.full", "summary.matchit")
+ return(res)
+}
+
+
+#' @export
+summary.matchit.subclass <- function(object, interactions = FALSE,
+ addlvariables=NULL, standardize = FALSE,
+ ...) {
+
+ X <- object$X
+ ## Fix X matrix so that it doesn't have any factors
+ varnames <- colnames(X)
+ for(var in varnames) {
+ if(is.factor(X[,var])) {
+ tempX <- X[,!colnames(X)%in%c(var)]
+ form<-formula(substitute(~dummy-1,list(dummy=as.name(var))))
+ X <- cbind(tempX, model.matrix(form, X))
+ }
+ }
+
+ XX <- cbind(distance=object$distance,X)
+ if (!is.null(addlvariables)) XX <- cbind(XX, addlvariables)
+
+ treat <- object$treat
+ weights <- object$weights
+ nam <- dimnames(XX)[[2]]
+ kk <- ncol(XX)
+
+ ## Summary Stats
+ aa <- apply(XX,2,qoi,tt=treat,ww=as.numeric(weights!=0),standardize=standardize)
+ sum.all <- as.data.frame(matrix(0,kk,6))
+ sum.matched <- as.data.frame(matrix(0,kk,6))
+ row.names(sum.all) <- row.names(sum.matched) <- nam
+ names(sum.all) <- names(sum.matched) <- names(aa[[1]])
+ sum.all.int <- sum.matched.int <- NULL
+ for(i in 1:kk){
+ sum.all[i,] <- aa[[i]][1,]
+ sum.matched[i,] <- aa[[i]][2,]
+ if(interactions){
+ for(j in i:kk){
+ x2 <- XX[,i]*as.matrix(XX[,j])
+ jqoi <- qoi(x2,tt=treat,ww=as.numeric(weights!=0),standardize=standardize)
+ sum.all.int <- rbind(sum.all.int,jqoi[1,])
+ sum.matched.int <- rbind(sum.matched.int,jqoi[2,])
+ row.names(sum.all.int)[nrow(sum.all.int)] <-
+ row.names(sum.matched.int)[nrow(sum.matched.int)] <-
+ paste(nam[i],nam[j],sep="x")
+ }
+ }
+ }
+ xn <- aa[[1]]$xn
+ sum.all <- rbind(sum.all,sum.all.int)
+ sum.matched <- rbind(sum.matched,sum.matched.int)
+
+ ## By Subclass
+ qbins <- max(object$subclass,na.rm=TRUE)
+ if(interactions){
+ q.table <- array(0,dim=c(kk+sum(1:kk),6,qbins))
+ ii <- 0
+ nn <- NULL
+ } else {
+ q.table <- array(0,dim=c(kk,6,qbins))
+ }
+ aa <- apply(XX,2,qoi.by.sub,tt=treat,ww=weights,
+ qq=object$subclass,standardize=standardize)
+ for(i in 1:kk){
+ if(!interactions){
+ q.table[i,,] <- as.matrix(aa[[i]]$q.table)
+ nn <- names(aa)
+ } else {
+ ii <- ii + 1
+ q.table[ii,,] <- as.matrix(aa[[i]]$q.table)
+ nn <- c(nn,names(aa)[i])
+ for(j in i:kk){
+ ii <- ii + 1
+ x2 <- XX[,i]*as.matrix(XX[,j])
+ q.table[ii,,] <- as.matrix(qoi.by.sub(x2,tt=treat,ww=weights,qq=object$subclass,
+ standardize=standardize)$q.table)
+ nn <- c(nn,paste(nam[i],nam[j],sep="x"))
+ }
+ }
+ }
+ qn <- aa[[1]]$qn
+ dimnames(q.table) <- list(nn,row.names(aa[[i]]$q.table),paste("Subclass",1:qbins))
+
+ ## Aggregate Subclass
+ if(is.null(object$call$sub.by)){
+ object$call$sub.by <- "treat"
+ }
+ if(object$call$sub.by=="treat") {
+ wsub <- qn[1,]/sum(qn[1,])
+ } else if(object$call$sub.by=="control") {
+ wsub <- qn[2,]/sum(qn[2,])
+ } else if(object$call$sub.by=="all") {
+ wsub <- qn[3,]/sum(qn[3,])
+ }
+ sum.subclass <- sum.all
+ for(i in 1:kk){
+ for(j in 1:6){
+ if(j==3) {
+ sum.subclass[i,j] <- sqrt(sum((wsub^2)*(q.table[i,j,]^2)))
+ } else {
+ sum.subclass[i,j] <- sum(wsub*q.table[i,j,])
+ }
+ }
+ }
+
+ ## Imbalance Reduction
+ stat0 <- abs(cbind(sum.all[,2]-sum.all[,1],
+ sum.all[,4:6]))
+ stat1 <- abs(cbind(sum.subclass[,2]-sum.subclass[,1],
+ sum.subclass[,4:6]))
+ reduction <- as.data.frame(100*(stat0-stat1)/stat0)
+ if(sum(stat0==0 & stat1==0, na.rm=T)>0){
+ reduction[stat0==0 & stat1==0] <- 0
+ }
+ if(sum(stat0==0 & stat1>0,na.rm=T)>0){
+ reduction[stat0==0 & stat1>0] <- -Inf
+ }
+ if (standardize)
+ names(reduction) <- c("Std. Mean Diff.", "eCDF Med","eCDF Mean",
+ "eCDF Max")
+ else
+ names(reduction) <- c("Mean Diff.", "eQQ Med","eQQ Mean",
+ "eQQ Max")
+ ## output
+ res <- list(call=object$call, sum.all = sum.all, sum.matched = sum.matched,
+ sum.subclass = sum.subclass, reduction = reduction,
+ qn = qn, q.table = q.table)
+ class(res) <- c("summary.matchit.subclass", "summary.matchit")
+ return(res)
+}
+
diff --git a/R/discard.R b/R/discard.R
index ecf6e5f..c1d222e 100644
--- a/R/discard.R
+++ b/R/discard.R
@@ -17,21 +17,16 @@ discard <- function(treat, pscore, option, X) {
discarded <- (pscore < pmin0 | pscore > pmax0)
else if (any(grep(option, c("hull.control", "hull.treat", "hull.both")))) {
## convext hull stuff
-# if (!("WhatIf" %in% .packages(all = TRUE)))
-# install.packages("WhatIf")
-# if (!("lpSolve" %in% .packages(all = TRUE)))
-# install.packages("lpSolve")
- require(WhatIf)
-# require(lpSolve)
+ requireNamespace("WhatIf")
discarded <- rep(FALSE, n.obs)
if (option == "hull.control"){ # discard units not in T convex hull
- wif <- whatif(cfact = X[treat==0,], data = X[treat==1,])
+ wif <- WhatIf::whatif(cfact = X[treat==0,], data = X[treat==1,])
discarded[treat==0] <- !wif$in.hull
} else if (option == "hull.treat") {
- wif <- whatif(cfact = X[treat==1,], data = X[treat==0,])
+ wif <- WhatIf::whatif(cfact = X[treat==1,], data = X[treat==0,])
discarded[treat==1] <- !wif$in.hull
} else if (option == "hull.both"){ # discard units not in T&C convex hull
- wif <- whatif(cfact = cbind(1-treat, X), data = cbind(treat, X))
+ wif <- WhatIf::whatif(cfact = cbind(1-treat, X), data = cbind(treat, X))
discarded <- !wif$in.hull
}
else
diff --git a/R/distance2GAM.R b/R/distance2GAM.R
index 862ba04..65557f2 100644
--- a/R/distance2GAM.R
+++ b/R/distance2GAM.R
@@ -1,30 +1,53 @@
distance2GAMlogit <- function(formula, data, ...) {
- require(mgcv)
- res <- gam(formula, data, family=binomial(logit), ...)
- return(list(model = res, distance = fitted(res)))
+ if (requireNamespace("mgcv", quietly = TRUE)) {
+ res <- mgcv::gam(formula, data, family=binomial(logit), ...)
+ return(list(model = res, distance = fitted(res)))
+ } else {
+ stop("mgcv package is needed. Please install it.",
+ call. = FALSE)
+ }
}
distance2GAMprobit <- function(formula, data, ...) {
- require(mgcv)
- res <- gam(formula, data, family=binomial(probit), ...)
- return(list(model = res, distance = fitted(res)))
+ if (requireNamespace("mgcv", quietly = TRUE)) {
+ res <- mgcv::gam(formula, data, family=binomial(probit), ...)
+ return(list(model = res, distance = fitted(res)))
+ } else {
+ stop("mgcv package is needed. Please install it.",
+ call. = FALSE)
+ }
}
distance2GAMcloglog <- function(formula, data, ...) {
- require(mgcv)
- res <- gam(formula, data, family=binomial(cloglog), ...)
- return(list(model = res, distance = fitted(res)))
+ if (requireNamespace("mgcv", quietly = TRUE)) {
+ res <- mgcv::gam(formula, data, family=binomial(cloglog), ...)
+ return(list(model = res, distance = fitted(res)))
+ } else {
+ stop("mgcv package is needed. Please install it.",
+ call. = FALSE)
+ }
}
+
distance2GAMlog <- function(formula, data, ...) {
- require(mgcv)
- res <- gam(formula, data, family=binomial(log), ...)
- return(list(model = res, distance = fitted(res)))
+ if (requireNamespace("mgcv", quietly = TRUE)) {
+ res <- mgcv::gam(formula, data, family=binomial(log), ...)
+ return(list(model = res, distance = fitted(res)))
+ } else {
+ stop("mgcv package is needed. Please install it.",
+ call. = FALSE)
+ }
}
+
distance2GAMcauchit <- function(formula, data, ...) {
- require(mgcv)
- res <- gam(formula, data, family=binomial(cauchit), ...)
- return(list(model = res, distance = fitted(res)))
+ if (requireNamespace("mgcv", quietly = TRUE)) {
+ res <- mgcv::gam(formula, data, family=binomial(cauchit), ...)
+ return(list(model = res, distance = fitted(res)))
+ } else {
+ stop("mgcv package is needed. Please install it.",
+ call. = FALSE)
+ }
}
+
diff --git a/R/distance2nnet.R b/R/distance2nnet.R
index e4d10ff..7338410 100644
--- a/R/distance2nnet.R
+++ b/R/distance2nnet.R
@@ -1,6 +1,10 @@
distance2nnet <- function(formula, data, ...) {
- require(nnet)
- res <- nnet(formula, data, ...)
- return(list(model = res, distance = fitted(res)))
+ if (requireNamespace("nnet", quietly = TRUE)) {
+ res <- nnet::nnet(formula, data, ...)
+ return(list(model = res, distance = fitted(res)))
+ } else {
+ stop("nnet package is needed. Please install it.",
+ call. = FALSE)
+ }
}
diff --git a/R/distance2rpart.R b/R/distance2rpart.R
index 091282d..289473b 100644
--- a/R/distance2rpart.R
+++ b/R/distance2rpart.R
@@ -1,6 +1,11 @@
distance2rpart <- function(formula, data, ...) {
- require(rpart)
- res <- rpart(formula, data, ...)
- return(list(model = res, distance = predict(res)))
+ if (requireNamespace("rpart", quietly = TRUE)) {
+ res <- rpart::rpart(formula, data, ...)
+ return(list(model = res, distance = predict(res)))
+ } else {
+ stop("rpart package is needed. Please install it.",
+ call. = FALSE)
+ }
}
+
diff --git a/R/help.matchit.R b/R/help.matchit.R
index c618d4c..3fe16ac 100644
--- a/R/help.matchit.R
+++ b/R/help.matchit.R
@@ -1,3 +1,4 @@
+#' @export
help.matchit <- function (object=NULL)
{
under.unix <- !(version$os == "Microsoft Windows" || version$os ==
diff --git a/R/match.data.R b/R/match.data.R
index 0cef1ba..5384d9e 100644
--- a/R/match.data.R
+++ b/R/match.data.R
@@ -1,3 +1,4 @@
+#' @export
match.data <- function(object, group = "all", distance = "distance",
weights = "weights", subclass = "subclass") {
diff --git a/R/matchit.R b/R/matchit.R
index f9f5557..4f39ba7 100644
--- a/R/matchit.R
+++ b/R/matchit.R
@@ -1,3 +1,4 @@
+#' @export
matchit <- function(formula, data, method = "nearest", distance = "logit",
distance.options=list(), discard = "none",
reestimate = FALSE, ...) {
@@ -36,7 +37,7 @@ matchit <- function(formula, data, method = "nearest", distance = "logit",
## obtain T and X
tryerror <- try(model.frame(formula), TRUE)
if (distance %in% c("GAMlogit", "GAMprobit", "GAMcloglog", "GAMlog", "GAMcauchit")) {
- library(mgcv)
+ requireNamespace("mgcv")
tt <- terms(mgcv::interpret.gam(formula)$fake.formula)
} else {
tt <- terms(formula)
diff --git a/R/matchit2cem.R b/R/matchit2cem.R
index b70af92..ee2fc5b 100644
--- a/R/matchit2cem.R
+++ b/R/matchit2cem.R
@@ -12,9 +12,8 @@ matchit2cem <- function(treat, X, data, distance, discarded, is.full.mahalanobis
ratio = 1, verbose = FALSE, k2k.method=NULL, ...) {
- #if (!("cem" %in% .packages(all = TRUE)))
- # install.packages("cem",repos="http://gking.harvard.edu/")
- require(cem)
+ if (!requireNamespace("cem", quietly = TRUE))
+ stop("cem package is required. Please install it.")
if (verbose)
cat("Coarsened exact matching...\n")
@@ -28,7 +27,7 @@ matchit2cem <- function(treat, X, data, distance, discarded, is.full.mahalanobis
cem.data <- as.data.frame(cbind(treat,X))
mat <-
- cem(treatment="treat",data=cem.data,verbose=as.integer(verbose)+1,
+ cem::cem(treatment="treat",data=cem.data,verbose=as.integer(verbose)+1,
method=k2k.method,...)
# here we create a column vector where the matched entry get its stratum
diff --git a/R/matchit2full.R b/R/matchit2full.R
index 5ca7169..5d6cf42 100644
--- a/R/matchit2full.R
+++ b/R/matchit2full.R
@@ -1,8 +1,5 @@
matchit2full <- function(treat, X, data, distance, discarded, is.full.mahalanobis,
verbose=FALSE, ...) {
- #if (!("optmatch" %in% .packages(all = TRUE)))
- # install.packages("optmatch")
- require(optmatch)
if(verbose)
cat("Full matching... \n")
@@ -19,7 +16,7 @@ matchit2full <- function(treat, X, data, distance, discarded, is.full.mahalanobi
colnames(d) <- names(ttt[ttt==0])
for (i in 1:n1)
d[i,] <- abs(d1[i]-d0)
- full <- fullmatch(d, ...)
+ full <- optmatch::fullmatch(d, ...)
psclass <- full[pmatch(names(ttt), names(full))]
psclass <- as.numeric(as.factor(psclass))
names(psclass) <- names(ttt)
diff --git a/R/matchit2genetic.R b/R/matchit2genetic.R
index 906301e..5feaa05 100644
--- a/R/matchit2genetic.R
+++ b/R/matchit2genetic.R
@@ -1,12 +1,5 @@
matchit2genetic <- function(treat, X, data, distance, discarded, is.full.mahalanobis,
ratio = 1, verbose = FALSE, ...) {
- #if (!("rgenoud" %in% .packages(all = TRUE)))
- # install.packages("rgenoud")
- #require(rgenoud)
-
- #if (!("Matching" %in% .packages(all = TRUE)))
- # install.packages("Matching")
- require(Matching)
if (verbose)
cat("Genetic matching... \n")
@@ -21,7 +14,7 @@ matchit2genetic <- function(treat, X, data, distance, discarded, is.full.mahalan
labels <- names(tt)
tlabels <- names(tt[tt==1])
clabels <- names(tt[tt==0])
- out <- GenMatch(tt, cbind(dd, xx), M = ratio, ...)$matches
+ out <- Matching::GenMatch(tt, cbind(dd, xx), M = ratio, ...)$matches
## ratio matching does not seem to work with GenMatch
mm <- matrix(0, nrow = n1, ncol = max(table(out[,1])), dimnames =
list(tlabels, 1:max(table(out[,1]))))
diff --git a/R/matchit2optimal.R b/R/matchit2optimal.R
index 22c97f9..a8227f7 100644
--- a/R/matchit2optimal.R
+++ b/R/matchit2optimal.R
@@ -1,9 +1,8 @@
matchit2optimal <- function(treat, X, data, distance, discarded, is.full.mahalanobis,
ratio = 1, verbose=FALSE, ...) {
- #if (!("optmatch" %in% .packages(all = TRUE)))
- # install.packages("optmatch")
- require(optmatch)
+ if (!requireNamespace("optmatch", quietly = TRUE))
+ stop("optmatch package is required. Please install it.")
if(verbose)
cat("Optimal matching... \n")
@@ -19,9 +18,9 @@ matchit2optimal <- function(treat, X, data, distance, discarded, is.full.mahalan
clabels <- colnames(d) <- names(ttt[ttt==0])
for (i in 1:n1)
d[i,] <- abs(d1[i]-d0)
- full <- fullmatch(d, min.controls = ratio,
- max.controls = ratio,
- omit.fraction = (n0-ratio*n1)/n0, ...)
+ full <- optmatch::fullmatch(d, min.controls = ratio,
+ max.controls = ratio,
+ omit.fraction = (n0-ratio*n1)/n0, ...)
psclass <- full[pmatch(names(ttt), names(full))]
psclass <- as.numeric(as.factor(psclass))
names(psclass) <- names(ttt)
diff --git a/R/plot.matchit.R b/R/plot.matchit.R
deleted file mode 100644
index 775502a..0000000
--- a/R/plot.matchit.R
+++ /dev/null
@@ -1,25 +0,0 @@
-# Need to account for weights -- how do we do qq plots with weights
-plot.matchit <- function(x, discrete.cutoff=5, type="QQ",
- numdraws=5000, interactive = T, which.xs =
- NULL, ...){
- if ("matchit.exact" %in% class(x)){
- stop("Not appropriate for exact matching. No plots generated.")
- }
- if(type=="QQ"){
- matchit.qqplot(x=x,discrete.cutoff=discrete.cutoff,
- numdraws=numdraws, interactive=interactive,
- which.xs = which.xs, ...)
- } else if(type=="jitter"){
- if("matchit.mahalanobis" %in% class(x)){
- stop("Not appropriate for pure Mahalanobis matching. No plots generated.")
- }
- jitter.pscore(x, interactive=interactive,...)
- } else if(type=="hist"){
- if("matchit.mahalanobis" %in% class(x)){
- stop("Not appropriate for pure Mahalanobis matching. No plots generated.")
- }
- hist.pscore(x,...)
- } else {
- stop("Invalid type")
- }
-}
diff --git a/R/plot.matchit.subclass.R b/R/plot.matchit.subclass.R
deleted file mode 100644
index ba13b23..0000000
--- a/R/plot.matchit.subclass.R
+++ /dev/null
@@ -1,45 +0,0 @@
-plot.matchit.subclass <- function(x, discrete.cutoff=5,
- type="QQ", interactive = T,
- subclass = NULL, which.xs=NULL,...){
- choice.menu <- function(choices,question)
- {
- k <- length(choices)-1
- Choices <- data.frame(choices)
- row.names(Choices) <- 0:k
- names(Choices) <- "Choices"
- print.data.frame(Choices,right=FALSE)
- ans <- readline(question)
- while(!ans%in%c(0:k))
- {
- print("Not valid -- please pick one of the choices")
- print.data.frame(Choices,right=FALSE)
- ans <- readline(question)
- }
- return(ans)
- }
- if(type=="QQ"){
- if(interactive){
- choices <- c("No",paste("Yes : Subclass ", 1:max(x$subclass,na.rm=T)))
- question <- "Would you like to see quantile-quantile plots of any subclasses?"
- ans <- -1
- while(ans!=0)
- {
- ans <- as.numeric(choice.menu(choices,question))
- if(ans!=0)
- {
- matchit.qqplot(x,discrete.cutoff,which.subclass=ans,
- interactive = interactive, which.xs=which.xs,...)
- }
- }
- } else {
- matchit.qqplot(x,discrete.cutoff,which.subclass=subclass,
- interactive=interactive, which.xs=which.xs,...)
- }
- } else if(type=="jitter"){
- jitter.pscore(x, interactive=interactive,...)
- } else if(type=="hist"){
- hist.pscore(x,...)
- } else {
- stop("Invalid type")
- }
-}
diff --git a/R/plot.summary.matchit.R b/R/plot.summary.matchit.R
deleted file mode 100644
index 601f87a..0000000
--- a/R/plot.summary.matchit.R
+++ /dev/null
@@ -1,42 +0,0 @@
-plot.summary.matchit <- function(x, interactive = TRUE, ...) {
- if ("matchit.exact" %in% class(x)){
- stop("Not appropriate for exact matching. No plots generated.")
- }
-
- if (!"Std. Mean Diff."%in%names(x$sum.all)){
- stop("Not appropriate for unstandardized summary. Run summary() with the standardize=TRUE option, and then plot.")
- }
-
- sd.pre <- abs(x$sum.all$"Std. Mean Diff.")
- sd.post <- abs(x$sum.matched$"Std. Mean Diff.")
-
- if (!is.null(x$q.table)) sd.post <- abs(x$sum.subclass$"Std. Mean Diff")
-
- ases.dat <- data.frame(es.unw = sd.pre, es.w = sd.post)
- par(mfrow=c(1,1))
- plot(c(0.85, 2.15), c(0, min(3, max(unlist(ases.dat[,
- 1:2]), na.rm = TRUE))), type = "n", xaxt = "n", ylab = "Absolute Standardized Diff in Means",
- xlab = "", main = "")
- abline(h = c(0.2, 0.4, 0.6, 0.8, 1.0))
- axis(side = 1, at = 1:2, labels = c("All Data", "Matched Data"))
- for (i in 1:nrow(ases.dat)) {
- points(1:2, abs(ases.dat[i, c("es.unw", "es.w")]),
- type = "b", col = "grey", pch=19)
- }
- temp1 <- ases.dat[abs(ases.dat$es.unw) < abs(ases.dat$es.w),]
- for (i in 1:nrow(temp1)) {
- points(1:2, abs(temp1[i, c("es.unw", "es.w")]), type = "b",
- col = "black", lwd = 2, pch=19)
- }
- if (max(ases.dat$es.w, na.rm = TRUE) > 3)
- mtext(text = "Some standardized diffs in means > 3 after matching!", side = 3,
- col = "red")
-
- if(interactive==TRUE) {
- print("To identify the variables, use first mouse button; to stop, use second.")
- identify(rep(1, length(sd.pre)),sd.pre,rownames(x$sum.all),atpen=T)
- identify(rep(2, length(sd.post)),sd.post,rownames(x$sum.all),atpen=T)
- }
-}
-
-
diff --git a/R/print.matchit.R b/R/print.matchit.R
deleted file mode 100644
index acc80d9..0000000
--- a/R/print.matchit.R
+++ /dev/null
@@ -1,16 +0,0 @@
-print.matchit <- function(x, digits = getOption("digits"), ...){
- cat("\nCall: ", deparse(x$call), sep="\n")
- cat("\nSample sizes:\n")
-
- #if(any(x$weights>0))
- # nn <- rbind(table(x$treat),
- # table(x$weights>0, x$treat),
- # c(0,0))
- #else
- # nn <- rbind(table(x$treat),
- # table(x$weights>0,x$treat)[2:1,])
-
- print.table(x$nn, ...)
- invisible(x)
- cat("\n")
-}
diff --git a/R/print.matchit.exact.R b/R/print.matchit.exact.R
deleted file mode 100644
index cfba1bc..0000000
--- a/R/print.matchit.exact.R
+++ /dev/null
@@ -1,16 +0,0 @@
-print.matchit.exact <- function(x, digits = getOption("digits"), ...){
- cat("\nCall: ", deparse(x$call), sep = "\n")
- cat("\nExact Subclasses: ", max(x$subclass, na.rm=T),"\n",sep="")
- cat("\nSample sizes:\n")
- ntab <- table(factor(!is.na(x$subclass),
- levels=c("TRUE","FALSE")),
- x$treat)
- nn <- rbind(table(x$treat),
- ntab[c("TRUE","FALSE"),])
- dimnames(nn) <- list(c("All","Matched","Unmatched"),
- c("Control","Treated"))
- print.table(nn, ...)
- invisible(x)
- cat("\n")
-}
-
diff --git a/R/print.matchit.full.R b/R/print.matchit.full.R
deleted file mode 100644
index 32c448a..0000000
--- a/R/print.matchit.full.R
+++ /dev/null
@@ -1,17 +0,0 @@
-print.matchit.full <- function(x, digits = getOption("digits"), ...){
- cat("\nCall: ", deparse(x$call), sep = "\n")
- cat("\nSample sizes:\n")
-
- if (any(x$weights>0))
- nn <- rbind(table(x$treat),
- table(x$weights>0, x$treat),
- c(0,0))
- else
- nn <- rbind(table(x$treat),
- table(x$weights>0,x$treat)[2:1,])
- dimnames(nn) <- list(c("All","Matched","Discarded"),
- c("Control","Treated"))
- print.table(nn, ...)
- invisible(x)
- cat("\n")
-}
diff --git a/R/print.matchit.subclass.R b/R/print.matchit.subclass.R
deleted file mode 100644
index 53e23ac..0000000
--- a/R/print.matchit.subclass.R
+++ /dev/null
@@ -1,12 +0,0 @@
-print.matchit.subclass <- function(x, digits = getOption("digits"), ...){
- cat("\nCall: ", deparse(x$call), sep = "\n")
- cat("\nSample sizes by subclasses:\n\n")
- nsub <- table(x$subclass,x$treat)
- nn <- rbind(table(x$treat),nsub)
- dimnames(nn) <-
- list(c("All",paste("Subclass",dimnames(nsub)[[1]])),
- c("Control","Treated"))
- print.table(nn, ...)
- invisible(x)
- cat("\n")
-}
diff --git a/R/print.summary.matchit.R b/R/print.summary.matchit.R
deleted file mode 100644
index 8b0803f..0000000
--- a/R/print.summary.matchit.R
+++ /dev/null
@@ -1,26 +0,0 @@
-print.summary.matchit <- function(x, digits = max(3,
- getOption("digits") - 3), ...){
-
- sum.all <- x$sum.all
- sum.matched <- x$sum.matched
- q.table <- x$q.table
- xn <- x$nn
- cat("\nCall:", deparse(x$call), sep = "\n")
- cat("\nSummary of balance for all data:\n")
- print.data.frame(round(sum.all,digits))
- cat("\n")
-
- xs1 <- sum.matched
- cc <- row.names(sum.all)
- if(!is.null(x$sum.matched) | identical(eval(x$call$method),"All"))
- {
- cat("\nSummary of balance for matched data:\n")
- print.data.frame(round(xs1,digits))
- cat("\nPercent Balance Improvement:\n")
- print.data.frame(round(x$reduction,digits))
- cat("\nSample sizes:\n")
- print.table(xn, digits=digits)
- cat("\n")
- }
- invisible(x)
-}
diff --git a/R/print.summary.matchit.exact.R b/R/print.summary.matchit.exact.R
deleted file mode 100644
index 85ab5d6..0000000
--- a/R/print.summary.matchit.exact.R
+++ /dev/null
@@ -1,11 +0,0 @@
-print.summary.matchit.exact <- function(x, digits = max(3,
- getOption("digits") - 3),
- ...){
- cat("\nCall:", deparse(x$call), sep = "\n")
- cat("\nSample sizes:\n")
- print.table(x$nn,digits=digits)
- cat("\nMatched sample sizes by subclass:\n")
- print.data.frame(x$q.table, digits = digits)
- cat("\n")
- invisible(x)
-}
diff --git a/R/print.summary.matchit.subclass.R b/R/print.summary.matchit.subclass.R
deleted file mode 100644
index eb29e1a..0000000
--- a/R/print.summary.matchit.subclass.R
+++ /dev/null
@@ -1,20 +0,0 @@
-print.summary.matchit.subclass <- function(x, digits = max(3,
- getOption("digits") -
- 3), ...){
- sum.all <- x$sum.all
- sum.matched <- x$sum.matched
- q.table <- x$q.table
- cat("\nCall:", deparse(x$call), sep = "\n")
- cat("Summary of balance for all data:\n")
- print.data.frame(round(sum.all,digits))
- cat("\n")
- cat("\nSummary of balance by subclasses:\n")
- print.table(round(q.table, digits))
- cat("\nSample sizes by subclasses:\n")
- print.data.frame(x$qn, digits = digits)
- cat("\nSummary of balance across subclasses\n")
- print.data.frame(round(x$sum.subclass, digits))
- cat("\nPercent Balance Improvement:\n")
- print.data.frame(round(x$reduction,digits))
- cat("\n")
-}
diff --git a/R/summary.matchit.R b/R/summary.matchit.R
deleted file mode 100644
index 5ca9137..0000000
--- a/R/summary.matchit.R
+++ /dev/null
@@ -1,82 +0,0 @@
-summary.matchit <- function(object, interactions = FALSE,
- addlvariables = NULL, standardize = FALSE,
- ...) {
-
- X <- object$X
- ## Fix X matrix so that it doesn't have any factors
- varnames <- colnames(X)
- for(var in varnames) {
- if(is.factor(X[,var])) {
- tempX <- X[,!colnames(X)%in%c(var)]
- form<-formula(substitute(~dummy-1,list(dummy=as.name(var))))
- X <- cbind(tempX, model.matrix(form, X))
- }
- }
-
- ## No distance output for pure Mahalanobis
- if("matchit.mahalanobis"%in%class(object)){
- XX <- X
- } else{
- XX <- cbind(distance=object$distance,X)
- }
- if (!is.null(addlvariables)) XX <- cbind(XX, addlvariables)
-
- treat <- object$treat
- weights <- object$weights
- nam <- dimnames(XX)[[2]]
- dupnam <- duplicated(nam)
- if(sum(dupnam)>0){
- nam[dupnam] <- paste(nam[dupnam],".1",sep="")
- }
- kk <- ncol(XX)
-
- ## Summary Stats
- aa <- apply(XX,2,qoi,tt=treat,ww=weights,standardize=standardize,std=T)
- sum.all <- as.data.frame(matrix(0,kk,7))
- sum.matched <- as.data.frame(matrix(0,kk,7))
- row.names(sum.all) <- row.names(sum.matched) <- nam
- names(sum.all) <- names(sum.matched) <- names(aa[[1]])
- sum.all.int <- sum.matched.int <- NULL
- for(i in 1:kk){
- sum.all[i,] <- aa[[i]][1,]
- sum.matched[i,] <- aa[[i]][2,]
- if(interactions){
- for(j in i:kk){
- x2 <- XX[,i]*as.matrix(XX[,j])
- jqoi <- qoi(x2,tt=treat,ww=weights,standardize=standardize,std=T)
- sum.all.int <- rbind(sum.all.int,jqoi[1,])
- sum.matched.int <- rbind(sum.matched.int,jqoi[2,])
- row.names(sum.all.int)[nrow(sum.all.int)] <-
- row.names(sum.matched.int)[nrow(sum.matched.int)] <-
- paste(nam[i],nam[j],sep="x")
- }
- }
- }
- xn <- aa[[1]]$xn
- sum.all <- rbind(sum.all,sum.all.int)
- sum.matched <- rbind(sum.matched,sum.matched.int)
-
- ## Imbalance Reduction
- stat0 <- abs(cbind(sum.all[,2]-sum.all[,1],
- sum.all[,5:7]))
- stat1 <- abs(cbind(sum.matched[,2]-sum.matched[,1],
- sum.matched[,5:7]))
- reduction <- as.data.frame(100*(stat0-stat1)/stat0)
- if(sum(stat0==0 & stat1==0, na.rm=T)>0){
- reduction[stat0==0 & stat1==0] <- 0
- }
- if(sum(stat0==0 & stat1>0,na.rm=T)>0){
- reduction[stat0==0 & stat1>0] <- -Inf
- }
- if (standardize)
- names(reduction) <- c("Std. Mean Diff.", "eCDF Med","eCDF Mean",
- "eCDF Max")
- else
- names(reduction) <- c("Mean Diff.", "eQQ Med","eQQ Mean", "eQQ Max")
-
- ## output
- res <- list(call=object$call, nn = object$nn, sum.all = sum.all,
- sum.matched = sum.matched, reduction = reduction)
- class(res) <- "summary.matchit"
- return(res)
-}
diff --git a/R/summary.matchit.exact.R b/R/summary.matchit.exact.R
deleted file mode 100644
index 8c66243..0000000
--- a/R/summary.matchit.exact.R
+++ /dev/null
@@ -1,34 +0,0 @@
-summary.matchit.exact <- function(object, covariates = FALSE, ...) {
- XX <- object$X
- treat <- object$treat
- qbins <- max(object$subclass,na.rm=TRUE)
- if(!covariates){
- q.table <- as.data.frame(matrix(0,qbins,3))
- names(q.table) <- c("Treated","Control","Total")
- for(i in 1:qbins){
- qi <- object$subclass==i
- q.table[i,] <- c(sum(treat[qi]==1, na.rm=T), sum(treat[qi]==0, na.rm=T),
- length(treat[qi & !is.na(qi)]))
- }
- } else {
- kk <- ncol(XX)
- q.table <- as.data.frame(matrix(0,qbins,kk+3))
- names(q.table) <- c("Treated","Control","Total",dimnames(XX)[[2]])
- for(i in 1:qbins){
- qi <- object$subclass==i & !is.na(object$subclass==i)
- q.table[i,] <- c(sum(treat[qi]==1, na.rm=T), sum(treat[qi]==0, na.rm=T),
- length(treat[qi & !is.na(qi)]),as.numeric(XX[qi,,drop=F][1,]))
- }
- }
- ntab <- table(factor(!is.na(object$subclass),
- levels=c("TRUE","FALSE")), treat)
- nn <- rbind(table(treat),
- ntab[c("TRUE","FALSE"),])
- dimnames(nn) <- list(c("All","Matched","Discarded"),
- c("Control","Treated"))
- ## output
- res <- list(q.table = q.table, nn = nn, subclass = object$subclass,
- treat = object$treat, call = object$call)
- class(res) <- c("summary.matchit.exact", "summary.matchit")
- return(res)
-}
diff --git a/R/summary.matchit.full.R b/R/summary.matchit.full.R
deleted file mode 100644
index 6652f5f..0000000
--- a/R/summary.matchit.full.R
+++ /dev/null
@@ -1,79 +0,0 @@
-summary.matchit.full <- function(object, interactions = FALSE,
- addlvariables = NULL, numdraws =
- 5000, standardize = FALSE,
- ...) {
-
- XX <- cbind(distance=object$distance,object$X)
- if (!is.null(addlvariables)) XX <- cbind(XX, addlvariables)
-
- treat <- object$treat
- weights <- object$weights
- nam <- dimnames(XX)[[2]]
- kk <- ncol(XX)
-
- ## Get samples of T and C units to send to qqplot
- t.plot <- sample(names(treat)[treat==1], numdraws/2, replace=TRUE, prob=weights[treat==1])
- c.plot <- sample(names(treat)[treat==0], numdraws/2, replace=TRUE, prob=weights[treat==0])
-
- ## Summary Stats
- aa <- apply(XX,2,qoi,tt=treat,ww=weights, t.plot=t.plot,
- c.plot=c.plot, standardize=standardize)
- sum.all <- as.data.frame(matrix(0,kk,6))
- sum.matched <- as.data.frame(matrix(0,kk,6))
- row.names(sum.all) <- row.names(sum.matched) <- nam
- names(sum.all) <- names(sum.matched) <- names(aa[[1]])
- sum.all.int <- sum.matched.int <- NULL
- for(i in 1:kk){
- sum.all[i,] <- aa[[i]][1,]
- sum.matched[i,] <- aa[[i]][2,]
- if(interactions){
- for(j in i:kk){
- x2 <- XX[,i]*as.matrix(XX[,j])
- names(x2) <- names(XX[,1])
- jqoi <- qoi(x2,tt=treat,ww=weights, t.plot=t.plot,
- c.plot=c.plot, standardize=standardize)
- sum.all.int <- rbind(sum.all.int,jqoi[1,])
- sum.matched.int <- rbind(sum.matched.int,jqoi[2,])
- row.names(sum.all.int)[nrow(sum.all.int)] <-
- row.names(sum.matched.int)[nrow(sum.matched.int)] <-
- paste(nam[i],nam[j],sep="x")
- }
- }
- }
- xn <- aa[[1]]$xn
- sum.all <- rbind(sum.all,sum.all.int)
- sum.matched <- rbind(sum.matched,sum.matched.int)
-
- ## Imbalance Reduction
- stat0 <- abs(cbind(sum.all[,2]-sum.all[,1],
- sum.all[,4:6]))
- stat1 <- abs(cbind(sum.matched[,2]-sum.matched[,1],
- sum.matched[,4:6]))
- reduction <- as.data.frame(100*(stat0-stat1)/stat0)
- if(sum(stat0==0 & stat1==0, na.rm=T)>0){
- reduction[stat0==0 & stat1==0] <- 0
- }
- if(sum(stat0==0 & stat1>0,na.rm=T)>0){
- reduction[stat0==0 & stat1>0] <- -Inf
- }
- if (standardize)
- names(reduction) <- c("Std. Mean Diff.", "eCDF Med","eCDF Mean", "eCDF Max")
- else
- names(reduction) <- c("Mean Diff.", "eQQ Med","eQQ Mean", "eQQ Max")
-
- ## Sample sizes
- nn <- matrix(0, ncol=2, nrow=4)
- nn[1,] <- c(sum(object$treat==0), sum(object$treat==1))
- nn[2,] <- c(sum(object$treat==0 & object$weights>0), sum(object$treat==1 & object$weights>0))
- nn[3,] <- c(sum(object$treat==0 & object$weights==0 & object$discarded==0), sum(object$treat==1 & object$weights==0 & object$discarded==0))
- nn[4,] <- c(sum(object$treat==0 & object$weights==0 & object$discarded==1), sum(object$treat==1 & object$weights==0 & object$discarded==1))
-
- dimnames(nn) <- list(c("All","Matched","Unmatched","Discarded"),
- c("Control","Treated"))
-
- ## output
- res <- list(call=object$call, nn = nn, sum.all = sum.all, sum.matched = sum.matched,
- reduction = reduction)
- class(res) <- c("summary.matchit.full", "summary.matchit")
- return(res)
-}
diff --git a/R/summary.matchit.subclass.R b/R/summary.matchit.subclass.R
deleted file mode 100644
index 3a9351f..0000000
--- a/R/summary.matchit.subclass.R
+++ /dev/null
@@ -1,126 +0,0 @@
-summary.matchit.subclass <- function(object, interactions = FALSE,
- addlvariables=NULL, standardize = FALSE,
- ...) {
-
- X <- object$X
- ## Fix X matrix so that it doesn't have any factors
- varnames <- colnames(X)
- for(var in varnames) {
- if(is.factor(X[,var])) {
- tempX <- X[,!colnames(X)%in%c(var)]
- form<-formula(substitute(~dummy-1,list(dummy=as.name(var))))
- X <- cbind(tempX, model.matrix(form, X))
- }
- }
-
- XX <- cbind(distance=object$distance,X)
- if (!is.null(addlvariables)) XX <- cbind(XX, addlvariables)
-
- treat <- object$treat
- weights <- object$weights
- nam <- dimnames(XX)[[2]]
- kk <- ncol(XX)
-
- ## Summary Stats
- aa <- apply(XX,2,qoi,tt=treat,ww=as.numeric(weights!=0),standardize=standardize)
- sum.all <- as.data.frame(matrix(0,kk,6))
- sum.matched <- as.data.frame(matrix(0,kk,6))
- row.names(sum.all) <- row.names(sum.matched) <- nam
- names(sum.all) <- names(sum.matched) <- names(aa[[1]])
- sum.all.int <- sum.matched.int <- NULL
- for(i in 1:kk){
- sum.all[i,] <- aa[[i]][1,]
- sum.matched[i,] <- aa[[i]][2,]
- if(interactions){
- for(j in i:kk){
- x2 <- XX[,i]*as.matrix(XX[,j])
- jqoi <- qoi(x2,tt=treat,ww=as.numeric(weights!=0),standardize=standardize)
- sum.all.int <- rbind(sum.all.int,jqoi[1,])
- sum.matched.int <- rbind(sum.matched.int,jqoi[2,])
- row.names(sum.all.int)[nrow(sum.all.int)] <-
- row.names(sum.matched.int)[nrow(sum.matched.int)] <-
- paste(nam[i],nam[j],sep="x")
- }
- }
- }
- xn <- aa[[1]]$xn
- sum.all <- rbind(sum.all,sum.all.int)
- sum.matched <- rbind(sum.matched,sum.matched.int)
-
- ## By Subclass
- qbins <- max(object$subclass,na.rm=TRUE)
- if(interactions){
- q.table <- array(0,dim=c(kk+sum(1:kk),6,qbins))
- ii <- 0
- nn <- NULL
- } else {
- q.table <- array(0,dim=c(kk,6,qbins))
- }
- aa <- apply(XX,2,qoi.by.sub,tt=treat,ww=weights,
- qq=object$subclass,standardize=standardize)
- for(i in 1:kk){
- if(!interactions){
- q.table[i,,] <- as.matrix(aa[[i]]$q.table)
- nn <- names(aa)
- } else {
- ii <- ii + 1
- q.table[ii,,] <- as.matrix(aa[[i]]$q.table)
- nn <- c(nn,names(aa)[i])
- for(j in i:kk){
- ii <- ii + 1
- x2 <- XX[,i]*as.matrix(XX[,j])
- q.table[ii,,] <- as.matrix(qoi.by.sub(x2,tt=treat,ww=weights,qq=object$subclass,standardize=standardize)$q.table)
- nn <- c(nn,paste(nam[i],nam[j],sep="x"))
- }
- }
- }
- qn <- aa[[1]]$qn
- dimnames(q.table) <- list(nn,row.names(aa[[i]]$q.table),paste("Subclass",1:qbins))
-
- ## Aggregate Subclass
- if(is.null(object$call$sub.by)){
- object$call$sub.by <- "treat"
- }
- if(object$call$sub.by=="treat") {
- wsub <- qn[1,]/sum(qn[1,])
- } else if(object$call$sub.by=="control") {
- wsub <- qn[2,]/sum(qn[2,])
- } else if(object$call$sub.by=="all") {
- wsub <- qn[3,]/sum(qn[3,])
- }
- sum.subclass <- sum.all
- for(i in 1:kk){
- for(j in 1:6){
- if(j==3) {
- sum.subclass[i,j] <- sqrt(sum((wsub^2)*(q.table[i,j,]^2)))
- } else {
- sum.subclass[i,j] <- sum(wsub*q.table[i,j,])
- }
- }
- }
-
- ## Imbalance Reduction
- stat0 <- abs(cbind(sum.all[,2]-sum.all[,1],
- sum.all[,4:6]))
- stat1 <- abs(cbind(sum.subclass[,2]-sum.subclass[,1],
- sum.subclass[,4:6]))
- reduction <- as.data.frame(100*(stat0-stat1)/stat0)
- if(sum(stat0==0 & stat1==0, na.rm=T)>0){
- reduction[stat0==0 & stat1==0] <- 0
- }
- if(sum(stat0==0 & stat1>0,na.rm=T)>0){
- reduction[stat0==0 & stat1>0] <- -Inf
- }
- if (standardize)
- names(reduction) <- c("Std. Mean Diff.", "eCDF Med","eCDF Mean",
- "eCDF Max")
- else
- names(reduction) <- c("Mean Diff.", "eQQ Med","eQQ Mean",
- "eQQ Max")
- ## output
- res <- list(call=object$call, sum.all = sum.all, sum.matched = sum.matched,
- sum.subclass = sum.subclass, reduction = reduction,
- qn = qn, q.table = q.table)
- class(res) <- c("summary.matchit.subclass", "summary.matchit")
- return(res)
-}
diff --git a/R/user.prompt.R b/R/user.prompt.R
index ca31067..d17d595 100644
--- a/R/user.prompt.R
+++ b/R/user.prompt.R
@@ -1,2 +1,3 @@
+#' @export
user.prompt <- function()
silent <- readline("\nPress <return> to continue: ")
diff --git a/README.md b/README.md
new file mode 100644
index 0000000..acf576e
--- /dev/null
+++ b/README.md
@@ -0,0 +1,3 @@
+# MatchIt: Nonparametric Preprocessing for Parametric Causal Inference [](https://travis-ci.org/kosukeimai/MatchIt) [](https://cran.r-project.org/package=MatchIt)
+
+MatchIt selects matched samples of the original treated and control groups with similar covariate distributions -- can be used to match exactly on covariates, to match on propensity scores, or perform a variety of other matching procedures. The package also implements a series of recommendations offered in Ho, Imai, King, and Stuart (2007) <[DOI:10.1093/pan/mpl013](https://doi.org/10.1093/pan/mpl013)>.
diff --git a/build/vignette.rds b/build/vignette.rds
new file mode 100644
index 0000000..3ccf52e
Binary files /dev/null and b/build/vignette.rds differ
diff --git a/inst/doc/matchit.pdf b/inst/doc/matchit.pdf
new file mode 100644
index 0000000..6cd3438
Binary files /dev/null and b/inst/doc/matchit.pdf differ
diff --git a/inst/doc/matchit.pdf.asis b/inst/doc/matchit.pdf.asis
new file mode 100644
index 0000000..0499143
--- /dev/null
+++ b/inst/doc/matchit.pdf.asis
@@ -0,0 +1,2 @@
+%\VignetteIndexEntry{MatchIt: Nonparametric Preprocessing for Parametric Causal Inference}
+%\VignetteEngine{R.rsp::asis}
diff --git a/man/get_matches.Rd b/man/get_matches.Rd
new file mode 100644
index 0000000..0f58075
--- /dev/null
+++ b/man/get_matches.Rd
@@ -0,0 +1,31 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/class_functions.R
+\name{get_matches}
+\alias{get_matches}
+\title{Get matches from matchit object}
+\usage{
+get_matches(object, model_frame, id_cols = NULL, newdata = NULL)
+}
+\arguments{
+\item{object}{The \code{'matchit'} class model object}
+
+\item{model_frame}{The \code{'data.frame'} class object used in creation of \code{object}.}
+
+\item{id_cols}{A string indicating the ID for the datset used in the call to \code{\link{matchit}}.
+This can be used in combination with \code{newdata} to return the base dataset. Defaults to
+\code{NULL}.}
+
+\item{newdata}{A new \code{data.frame} object to extract matched observations from. Used in
+conjunction with \code{id_cols}. Defaults to \code{NULL}.}
+}
+\value{
+If \code{newdata} is \code{NULL}, a subset of \code{model_frame} containing the rows
+corresponding to the matched treatement and control observations with weights appended. If
+\code{newdata} is not \code{NULL}, an equivalent subset of \code{newdata} is returned.
+}
+\description{
+Get the resulting matches from a \code{matchit} model object. This function allows the
+user to extract the matches from the original dataset used in model building or from a new dataset
+that has a matching set of key column(s) (\code{id_cols}).
+}
+
diff --git a/man/is.matchit.Rd b/man/is.matchit.Rd
new file mode 100644
index 0000000..722cda6
--- /dev/null
+++ b/man/is.matchit.Rd
@@ -0,0 +1,19 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/class_functions.R
+\name{is.matchit}
+\alias{is.matchit}
+\title{Checks matchit Class}
+\usage{
+is.matchit(object)
+}
+\arguments{
+\item{object}{any R object}
+}
+\value{
+Returns \code{TRUE} if its argument has class "matchit" among its classes and
+\code{FALSE} otherwise.
+}
+\description{
+Function that checks if the target object is a \code{matchit} object.
+}
+
diff --git a/man/lalonde.Rd b/man/lalonde.Rd
index b597909..38a9e04 100644
--- a/man/lalonde.Rd
+++ b/man/lalonde.Rd
@@ -5,8 +5,7 @@
\description{ This is a subsample of the data from the treated group in the National Supported
Work Demonstration (NSW) and the comparison sample from the Current Population Survey (CPS).
-This data was previously analyzed extensively by Lalonde (1986) and Dehejia and Wahba (1999).
-The full dataset is available at \url{http://www.columbia.edu/~rd247/nswdata.html}. }
+This data was previously analyzed extensively by Lalonde (1986) and Dehejia and Wahba (1999). }
\usage{data(lalonde)}
@@ -27,5 +26,5 @@ dollars. "re78" is income in 1978, in U.S. dollars. }
Re-Evaluating the Evaluation of Training Programs. Journal of the American
Statistical Association 94: 1053-1062.
}
-\source{\url{http://www.columbia.edu/~rd247/nswdata.html}}
+
\keyword{datasets}
diff --git a/tests/testthat.R b/tests/testthat.R
new file mode 100644
index 0000000..4b29f57
--- /dev/null
+++ b/tests/testthat.R
@@ -0,0 +1,4 @@
+library(testthat)
+library(MatchIt)
+
+test_check("MatchIt")
diff --git a/tests/testthat/test-get_matches.R b/tests/testthat/test-get_matches.R
new file mode 100644
index 0000000..84c035b
--- /dev/null
+++ b/tests/testthat/test-get_matches.R
@@ -0,0 +1,289 @@
+
+library(testthat)
+library(MatchIt)
+
+data("lalonde")
+
+context("get_matches")
+
+test_that("can get correct matches, exact", {
+ # preliminaries
+ m.out <- matchit(treat ~ educ + black + hispan, data = lalonde,
+ method = "exact")
+ n_matched <- sum(m.out$nn[2,])
+ nms_matched <- names(m.out$subclass[!is.na(m.out$subclass)])
+
+ lalonde$id <- 1:nrow(lalonde)
+ lalonde2 <- lalonde[sample.int(500, 3000, replace=TRUE),]
+ matches <- get_matches(m.out, lalonde)
+ matches2 <- get_matches(m.out, model_frame= lalonde, id_cols= "id", newdata= lalonde2)
+
+ # tests -- no newdata
+ expect_equal(n_matched, nrow(matches))
+ expect_equal(sum(matches$treat), m.out$nn[2,2])
+ expect_equal(nrow(matches) - sum(matches$treat), m.out$nn[2,1])
+ expect_equal(sum(is.na(matches)), 0L)
+ expect_equal(names(matches), c(names(lalonde), "weight"))
+ expect_equal(ncol(matches), ncol(lalonde) + 1)
+ expect_true(all(matches[matches$treat == 1,]$weight == 1))
+ expect_true(all(matches$weight %in% m.out$weights))
+ expect_true(all(rownames(matches) %in% nms_matched))
+ expect_true(all(nms_matched %in% rownames(matches)))
+
+ # tests -- newdata
+ expect_equal(sum(is.na(matches2)), 0L)
+ expect_true(all(names(matches2) %in% c(names(lalonde2), "weight")))
+ expect_true(all(c(names(lalonde2), "weight") %in% names(matches2)))
+ expect_equal(ncol(matches2), ncol(lalonde2) + 1)
+ expect_true(all(matches2[matches2$treat == 1,]$weight == 1))
+ expect_true(all(matches2$weight %in% m.out$weights))
+})
+
+test_that("can get correct matches, nearest", {
+ m.out <- matchit(treat ~ re74 + re75 + educ + black + hispan + age,
+ data = lalonde, method = "nearest")
+ n_matched <- sum(m.out$nn[2,])
+ nms_matched <- c(rownames(m.out$match.matrix), c(m.out$match.matrix))
+
+ lalonde$id <- 1:nrow(lalonde)
+ lalonde2 <- lalonde[sample.int(500, 3000, replace=TRUE),]
+ matches <- get_matches(m.out, lalonde)
+ matches2 <- get_matches(m.out, model_frame= lalonde, id_cols= "id", newdata= lalonde2)
+
+ # tests -- no newdata
+ expect_equal(n_matched, nrow(matches))
+ expect_equal(sum(matches$treat), m.out$nn[2,2])
+ expect_equal(nrow(matches) - sum(matches$treat), m.out$nn[2,1])
+ expect_equal(sum(is.na(matches)), 0L)
+ expect_equal(names(matches), c(names(lalonde), "weight"))
+ expect_equal(ncol(matches), ncol(lalonde) + 1)
+ expect_true(all(matches[matches$treat == 1,]$weight == 1))
+ expect_true(all(matches$weight %in% m.out$weights))
+ expect_true(all(rownames(matches) %in% nms_matched))
+ expect_true(all(nms_matched %in% rownames(matches)))
+
+ # tests -- newdata
+ expect_equal(sum(is.na(matches2)), 0L)
+ expect_true(all(names(matches2) %in% c(names(lalonde2), "weight")))
+ expect_true(all(c(names(lalonde2), "weight") %in% names(matches2)))
+ expect_equal(ncol(matches2), ncol(lalonde2) + 1)
+ expect_true(all(matches2[matches2$treat == 1,]$weight == 1))
+ expect_true(all(matches2$weight %in% m.out$weights))
+
+})
+
+
+test_that("can get correct matches, full", {
+ # preliminaries
+ m.out <- matchit(treat ~ age + educ + black + hispan + married +
+ nodegree + re74 + re75, data = lalonde, method = "full")
+ n_matched <- sum(m.out$nn[2,])
+ nms_matched <- names(m.out$subclass[!is.na(m.out$subclass)])
+
+ lalonde$id <- 1:nrow(lalonde)
+ lalonde2 <- lalonde[sample.int(500, 3000, replace=TRUE),]
+ matches <- get_matches(m.out, lalonde)
+ matches2 <- get_matches(m.out, model_frame= lalonde, id_cols= "id", newdata= lalonde2)
+
+ # tests -- no newdata
+ expect_equal(n_matched, nrow(matches))
+ expect_equal(sum(matches$treat), m.out$nn[2,2])
+ expect_equal(nrow(matches) - sum(matches$treat), m.out$nn[2,1])
+ expect_equal(sum(is.na(matches)), 0L)
+ expect_equal(names(matches), c(names(lalonde), "weight"))
+ expect_equal(ncol(matches), ncol(lalonde) + 1)
+ expect_true(all(matches[matches$treat == 1,]$weight == 1))
+ expect_true(all(matches$weight %in% m.out$weights))
+ expect_true(all(rownames(matches) %in% nms_matched))
+ expect_true(all(nms_matched %in% rownames(matches)))
+
+ # tests -- newdata
+ expect_equal(sum(is.na(matches2)), 0L)
+ expect_true(all(names(matches2) %in% c(names(lalonde2), "weight")))
+ expect_true(all(c(names(lalonde2), "weight") %in% names(matches2)))
+ expect_equal(ncol(matches2), ncol(lalonde2) + 1)
+ expect_true(all(matches2[matches2$treat == 1,]$weight == 1))
+ expect_true(all(matches2$weight %in% m.out$weights))
+})
+
+
+test_that("can get correct matches, optimal", {
+ ratio <- 2
+ m.out <- matchit(treat ~ re74 + re75 + age + educ, data = lalonde,
+ method = "optimal", ratio = ratio)
+ n_matched <- sum(m.out$nn[2,])
+ nms_matched <- c(rownames(m.out$match.matrix), c(m.out$match.matrix))
+
+ lalonde$id <- 1:nrow(lalonde)
+ lalonde2 <- lalonde[sample.int(500, 3000, replace=TRUE),]
+ matches <- get_matches(m.out, lalonde)
+ matches2 <- get_matches(m.out, model_frame= lalonde, id_cols= "id", newdata= lalonde2)
+
+ # tests -- no newdata
+ expect_equal(n_matched, nrow(matches))
+ expect_equal(sum(matches$treat), m.out$nn[2,2])
+ expect_equal(nrow(matches) - sum(matches$treat), m.out$nn[2,1])
+ expect_equal(sum(is.na(matches)), 0L)
+ expect_equal(names(matches), c(names(lalonde), "weight"))
+ expect_equal(ncol(matches), ncol(lalonde) + 1)
+ expect_true(all(matches[matches$treat == 1,]$weight == 1))
+ expect_true(all(matches$weight %in% c(1, 1 / ratio)))
+ expect_true(all(rownames(matches) %in% nms_matched))
+ expect_true(all(nms_matched %in% rownames(matches)))
+
+ # tests -- newdata
+ expect_equal(sum(is.na(matches2)), 0L)
+ expect_true(all(names(matches2) %in% c(names(lalonde2), "weight")))
+ expect_true(all(c(names(lalonde2), "weight") %in% names(matches2)))
+ expect_equal(ncol(matches2), ncol(lalonde2) + 1)
+ expect_true(all(matches2[matches2$treat == 1,]$weight == 1))
+ expect_true(all(matches2$weight %in% c(1, 1 / ratio)))
+})
+
+
+test_that("can get correct matches, subclass", {
+ m.out <- matchit(treat ~ re74 + re75 + educ + black + hispan + age,
+ data = lalonde, method = "subclass")
+ n_matched <- sum(m.out$nn[2,])
+ nms_matched <- names(m.out$subclass[!is.na(m.out$subclass)])
+
+ lalonde$id <- 1:nrow(lalonde)
+ lalonde2 <- lalonde[sample.int(500, 3000, replace=TRUE),]
+ matches <- get_matches(m.out, lalonde)
+ matches2 <- get_matches(m.out, model_frame= lalonde, id_cols= "id", newdata= lalonde2)
+
+ # tests -- no newdata
+ expect_equal(n_matched, nrow(matches))
+ expect_equal(sum(matches$treat), m.out$nn[2,2])
+ expect_equal(nrow(matches) - sum(matches$treat), m.out$nn[2,1])
+ expect_equal(sum(is.na(matches)), 0L)
+ expect_equal(names(matches), c(names(lalonde), "weight"))
+ expect_equal(ncol(matches), ncol(lalonde) + 1)
+ expect_true(all(matches[matches$treat == 1,]$weight == 1))
+ expect_true(all(matches$weight %in% m.out$weights))
+ expect_true(all(rownames(matches) %in% nms_matched))
+ expect_true(all(nms_matched %in% rownames(matches)))
+
+ # tests -- newdata
+ expect_equal(sum(is.na(matches2)), 0L)
+ expect_true(all(names(matches2) %in% c(names(lalonde2), "weight")))
+ expect_true(all(c(names(lalonde2), "weight") %in% names(matches2)))
+ expect_equal(ncol(matches2), ncol(lalonde2) + 1)
+ expect_true(all(matches2[matches2$treat == 1,]$weight == 1))
+ expect_true(all(matches2$weight %in% m.out$weights))
+})
+
+test_that("can get correct matches, genetic", { ## this one is problematic -- problematic returns
+ m.out <- matchit(treat ~ age + educ + black + hispan + married + nodegree +
+ re74 + re75, data = lalonde, method = "genetic")
+ n_matched <- sum(m.out$nn[2,])
+ nms_matched <- c(rownames(m.out$match.matrix), m.out$match.matrix[,1],
+ m.out$match.matrix[which(!is.na(m.out$match.matrix[,2])), 2])
+
+ lalonde$id <- 1:nrow(lalonde)
+ lalonde2 <- lalonde[sample.int(500, 3000, replace=TRUE),]
+ matches <- get_matches(m.out, lalonde)
+ matches2 <- get_matches(m.out, model_frame= lalonde, id_cols= "id", newdata= lalonde2)
+
+ # tests -- no newdata
+ expect_equal(n_matched, nrow(matches))
+ expect_equal(sum(matches$treat), m.out$nn[2,2])
+ expect_equal(nrow(matches) - sum(matches$treat), m.out$nn[2,1])
+ expect_equal(sum(is.na(matches)), 0L)
+ expect_equal(names(matches), c(names(lalonde), "weight"))
+ expect_equal(ncol(matches), ncol(lalonde) + 1)
+ expect_true(all(matches[matches$treat == 1,]$weight == 1))
+ expect_true(all(rownames(matches) %in% nms_matched))
+ expect_true(all(nms_matched %in% rownames(matches)))
+
+ # tests -- newdata
+ expect_equal(sum(is.na(matches2)), 0L)
+ expect_true(all(names(matches2) %in% c(names(lalonde2), "weight")))
+ expect_true(all(c(names(lalonde2), "weight") %in% names(matches2)))
+ expect_equal(ncol(matches2), ncol(lalonde2) + 1)
+ expect_true(all(matches2[matches2$treat == 1,]$weight == 1))
+})
+
+test_that("can get correct matches, cem", {
+ library(cem)
+ m.out <- matchit(treat ~ age + educ + black + hispan + married + nodegree
+ + re74 + re75, data = lalonde, method = "cem")
+ n_matched <- sum(m.out$nn[2,])
+ nms_matched <- names(m.out$subclass[!is.na(m.out$subclass)])
+
+ lalonde$id <- 1:nrow(lalonde)
+ lalonde2 <- lalonde[sample.int(500, 3000, replace=TRUE),]
+ matches <- get_matches(m.out, lalonde)
+ matches2 <- get_matches(m.out, model_frame= lalonde, id_cols= "id", newdata= lalonde2)
+
+ # tests -- no newdata
+ expect_equal(n_matched, nrow(matches))
+ expect_equal(sum(matches$treat), m.out$nn[2,2])
+ expect_equal(nrow(matches) - sum(matches$treat), m.out$nn[2,1])
+ expect_equal(sum(is.na(matches)), 0L)
+ expect_equal(names(matches), c(names(lalonde), "weight"))
+ expect_equal(ncol(matches), ncol(lalonde) + 1)
+ expect_true(all(matches[matches$treat == 1,]$weight == 1))
+ expect_true(all(matches$weight %in% m.out$weights))
+ expect_true(all(rownames(matches) %in% nms_matched))
+ expect_true(all(nms_matched %in% rownames(matches)))
+
+ # tests -- newdata
+ expect_equal(sum(is.na(matches2)), 0L)
+ expect_true(all(names(matches2) %in% c(names(lalonde2), "weight")))
+ expect_true(all(c(names(lalonde2), "weight") %in% names(matches2)))
+ expect_equal(ncol(matches2), ncol(lalonde2) + 1)
+ expect_true(all(matches2[matches2$treat == 1,]$weight == 1))
+ expect_true(all(matches2$weight %in% m.out$weights))
+
+})
+
+l_treat <- do.call("rbind",replicate(10, lalonde[lalonde$treat == 1, ], simplify = FALSE))
+l_contr <- do.call("rbind",replicate(3, lalonde[lalonde$treat == 0, ], simplify = FALSE))
+l2 <- do.call("rbind", list(l_treat, l_contr)); rm(l_treat, l_contr)
+rownames(l2) <- 1:nrow(l2)
+
+test_that("correct weights for replace= TRUE", {
+ m.out <- matchit(treat ~ re74 + re75 + educ + black + hispan + age,
+ data = l2, method = "nearest", replace= TRUE)
+ n_matched <- sum(m.out$nn[2,])
+ nms_matched <- c(rownames(m.out$match.matrix), c(m.out$match.matrix))
+
+ matches <- get_matches(m.out, l2)
+ exp_wts <- c(1, unique(as.vector(table(m.out$match.matrix))))
+
+ # tests -- no newdata
+ expect_equal(n_matched, nrow(matches))
+ expect_equal(sum(matches$treat), m.out$nn[2,2])
+ expect_equal(nrow(matches) - sum(matches$treat), m.out$nn[2,1])
+ expect_equal(sum(is.na(matches)), 0L)
+ expect_equal(names(matches), c(names(lalonde), "weight"))
+ expect_equal(ncol(matches), ncol(lalonde) + 1)
+ expect_true(all(matches[matches$treat == 1,]$weight == 1))
+ expect_true(all(matches$weight %in% exp_wts))
+ expect_true(all(rownames(matches) %in% nms_matched))
+ expect_true(all(nms_matched %in% rownames(matches)))
+})
+
+
+test_that("correct weights for replace= TRUE; test2", {
+ m.out <- matchit(treat ~ re74 + re75 + educ + black + hispan + age,
+ data = l2, method = "cem")
+ n_matched <- sum(m.out$nn[2,])
+ nms_matched <- names(m.out$subclass[!is.na(m.out$subclass)])
+
+ matches <- get_matches(m.out, l2)
+ exp_wts <- c(1, unique(as.vector(table(m.out$match.matrix))))
+
+ # tests -- no newdata
+ expect_equal(n_matched, nrow(matches))
+ expect_equal(sum(matches$treat), m.out$nn[2,2])
+ expect_equal(nrow(matches) - sum(matches$treat), m.out$nn[2,1])
+ expect_equal(sum(is.na(matches)), 0L)
+ expect_equal(names(matches), c(names(lalonde), "weight"))
+ expect_equal(ncol(matches), ncol(lalonde) + 1)
+ expect_true(all(matches[matches$treat == 1,]$weight == 1))
+ expect_true(all(matches$weight %in% m.out$weights))
+ expect_true(all(rownames(matches) %in% nms_matched))
+ expect_true(all(nms_matched %in% rownames(matches)))
+})
diff --git a/vignettes/Makefile b/vignettes/Makefile
deleted file mode 100755
index b338f6c..0000000
--- a/vignettes/Makefile
+++ /dev/null
@@ -1,10 +0,0 @@
-all:
- pdflatex matchit
- bibtex matchit
- pdflatex matchit
- pdflatex matchit
-matchit.pdf:
- pdflatex matchit
- bibtex matchit
- pdflatex matchit
- pdflatex matchit
diff --git a/vignettes/asa.bst b/vignettes/asa.bst
deleted file mode 100644
index 4e12e00..0000000
--- a/vignettes/asa.bst
+++ /dev/null
@@ -1,1505 +0,0 @@
-%%
-%% This is file `asa.bst',
-%% generated with the docstrip utility.
-%%
-%% The original source files were:
-%%
-%% merlin.mbs (with options: `,ay,nat,nm-rev,ed-rev,nmdash,dt-beg,yr-par,note-yr,tit-qq,atit-u,thtit-a,vnum-x,volp-com,pp-last,add-pub,pre-pub,edpar,edby,edbyx,blk-com,pp,ed,abr,ednx,ord,em-it,nfss')
-%% ----------------------------------------
-%% *** BibTeX Style for ASA Journals ***
-%% (Brett Presnell, 24 August 1998)
-%%
- %-------------------------------------------------------------------
- % The original source file contains the following version information:
- % \ProvidesFile{merlin.mbs}[1998/02/25 3.85a (PWD)]
- %
- % NOTICE:
- % This file may be used for non-profit purposes.
- % It may not be distributed in exchange for money,
- % other than distribution costs.
- %
- % The author provides it `as is' and does not guarantee it in any way.
- %
- % Copyright (C) 1994-98 Patrick W. Daly
- %-------------------------------------------------------------------
- % For use with BibTeX version 0.99a or later
- %-------------------------------------------------------------------
- % This bibliography style file is intended for texts in ENGLISH
- % This is an author-year citation style bibliography. As such, it is
- % non-standard LaTeX, and requires a special package file to function properly.
- % Such a package is natbib.sty by Patrick W. Daly
- % The form of the \bibitem entries is
- % \bibitem[Jones et al.(1990)]{key}...
- % \bibitem[Jones et al.(1990)Jones, Baker, and Smith]{key}...
- % The essential feature is that the label (the part in brackets) consists
- % of the author names, as they should appear in the citation, with the year
- % in parentheses following. There must be no space before the opening
- % parenthesis!
- % With natbib v5.3, a full list of authors may also follow the year.
- % In natbib.sty, it is possible to define the type of enclosures that is
- % really wanted (brackets or parentheses), but in either case, there must
- % be parentheses in the label.
- % The \cite command functions as follows:
- % \citet{key} ==>> Jones et al. (1990)
- % \citet*{key} ==>> Jones, Baker, and Smith (1990)
- % \citep{key} ==>> (Jones et al., 1990)
- % \citep*{key} ==>> (Jones, Baker, and Smith, 1990)
- % \citep[chap. 2]{key} ==>> (Jones et al., 1990, chap. 2)
- % \citep[e.g.][]{key} ==>> (e.g. Jones et al., 1990)
- % \citep[e.g.][p. 32]{key} ==>> (e.g. Jones et al., p. 32)
- % \citeauthor{key} ==>> Jones et al.
- % \citeauthor*{key} ==>> Jones, Baker, and Smith
- % \citeyear{key} ==>> 1990
- %---------------------------------------------------------------------
-
-ENTRY
- { address
- author
- booktitle
- chapter
- edition
- editor
- howpublished
- institution
- journal
- key
- month
- note
- number
- organization
- pages
- publisher
- school
- series
- title
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- volume
- year
- }
- {}
- { label extra.label sort.label short.list }
-
-INTEGERS { output.state before.all mid.sentence after.sentence after.block }
-
-FUNCTION {init.state.consts}
-{ #0 'before.all :=
- #1 'mid.sentence :=
- #2 'after.sentence :=
- #3 'after.block :=
-}
-
-STRINGS { s t }
-
-FUNCTION {output.nonnull}
-{ 's :=
- output.state mid.sentence =
- { ", " * write$ }
- { output.state after.block =
- { add.period$ write$
- newline$
- "\newblock " write$
- }
- { output.state before.all =
- 'write$
- { add.period$ " " * write$ }
- if$
- }
- if$
- mid.sentence 'output.state :=
- }
- if$
- s
-}
-
-FUNCTION {output}
-{ duplicate$ empty$
- 'pop$
- 'output.nonnull
- if$
-}
-
-FUNCTION {output.check}
-{ 't :=
- duplicate$ empty$
- { pop$ "empty " t * " in " * cite$ * warning$ }
- 'output.nonnull
- if$
-}
-
-FUNCTION {fin.entry}
-{ add.period$
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- newline$
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-
-FUNCTION {new.block}
-{ output.state before.all =
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-FUNCTION {new.sentence}
-{ output.state after.block =
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- 'skip$
- { after.sentence 'output.state := }
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-FUNCTION {add.blank}
-{ " " * before.all 'output.state :=
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-FUNCTION {date.block}
-{
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-{ { #0 }
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-{ { pop$ #1 }
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-{ duplicate$
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-{ empty$
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-{ duplicate$ empty$
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-{ "u" change.case$ "t" change.case$ }
-
-FUNCTION {space.word}
-{ " " swap$ * " " * }
-
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- % Each function has a name bbl.xxx where xxx is the English word.
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-{ "and"}
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-FUNCTION {bbl.editors}
-{ "eds." }
-
-FUNCTION {bbl.editor}
-{ "ed." }
-
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-{ "edited by" }
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-FUNCTION {bbl.edition}
-{ "ed." }
-
-FUNCTION {bbl.volume}
-{ "vol." }
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-{ "of" }
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-{ "no." }
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-{ "no." }
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-{ "in" }
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-FUNCTION {bbl.pages}
-{ "pp." }
-
-FUNCTION {bbl.page}
-{ "p." }
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-FUNCTION {bbl.chapter}
-{ "chap." }
-
-FUNCTION {bbl.techrep}
-{ "Tech. Rep." }
-
-FUNCTION {bbl.mthesis}
-{ "Master's thesis" }
-
-FUNCTION {bbl.phdthesis}
-{ "Ph.D. thesis" }
-
-FUNCTION {bbl.first}
-{ "1st" }
-
-FUNCTION {bbl.second}
-{ "2nd" }
-
-FUNCTION {bbl.third}
-{ "3rd" }
-
-FUNCTION {bbl.fourth}
-{ "4th" }
-
-FUNCTION {bbl.fifth}
-{ "5th" }
-
-FUNCTION {bbl.st}
-{ "st" }
-
-FUNCTION {bbl.nd}
-{ "nd" }
-
-FUNCTION {bbl.rd}
-{ "rd" }
-
-FUNCTION {bbl.th}
-{ "th" }
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-MACRO {jan} {"Jan."}
-
-MACRO {feb} {"Feb."}
-
-MACRO {mar} {"Mar."}
-
-MACRO {apr} {"Apr."}
-
-MACRO {may} {"May"}
-
-MACRO {jun} {"Jun."}
-
-MACRO {jul} {"Jul."}
-
-MACRO {aug} {"Aug."}
-
-MACRO {sep} {"Sep."}
-
-MACRO {oct} {"Oct."}
-
-MACRO {nov} {"Nov."}
-
-MACRO {dec} {"Dec."}
-
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-{ duplicate$ "1" swap$ *
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- duplicate$ "1" =
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-
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-
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-
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-
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-
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-
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-
-MACRO {ieeetcad}
- {"IEEE Transactions on Computer-Aided Design of Integrated Circuits"}
-
-MACRO {ipl} {"Information Processing Letters"}
-
-MACRO {jacm} {"Journal of the ACM"}
-
-MACRO {jcss} {"Journal of Computer and System Sciences"}
-
-MACRO {scp} {"Science of Computer Programming"}
-
-MACRO {sicomp} {"SIAM Journal on Computing"}
-
-MACRO {tocs} {"ACM Transactions on Computer Systems"}
-
-MACRO {tods} {"ACM Transactions on Database Systems"}
-
-MACRO {tog} {"ACM Transactions on Graphics"}
-
-MACRO {toms} {"ACM Transactions on Mathematical Software"}
-
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-
-MACRO {toplas} {"ACM Transactions on Programming Languages and Systems"}
-
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-
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- }
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- 't
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-{ format.names }
-FUNCTION {format.key}
-{ empty$
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- if$
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-FUNCTION {format.authors}
-{ author empty$
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- { " (" * bbl.editor * ")" * }
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-{ editor empty$
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- if$
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-
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-{ note empty$
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- duplicate$ "{" =
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- { output.state mid.sentence =
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- non.stop
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- { "} " * }
- if$
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- if$
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-
-FUNCTION {end.quote.title}
-{ title empty$
- 'skip$
- { before.all 'output.state := }
- if$
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-
-FUNCTION {format.full.names}
-{'s :=
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- { namesleft #0 > }
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- "{vv~}{ll}" format.name$
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- namesleft #1 >
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- {
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- { "," * }
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- t "others" =
- {
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- if$
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- 't
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-{ author empty$
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- 'key
- if$
- }
- { author format.full.names }
- if$
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-
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-{ editor empty$
- { key empty$
- { cite$ #1 #3 substring$ }
- 'key
- if$
- }
- { editor format.full.names }
- if$
-}
-
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-{ type$ "book" =
- type$ "inbook" =
- or
- 'author.editor.key.full
- { type$ "proceedings" =
- 'editor.key.full
- 'author.key.full
- if$
- }
- if$
-}
-
-FUNCTION {output.bibitem}
-{ newline$
- "\bibitem[{" write$
- label write$
- ")" make.full.names duplicate$ short.list =
- { pop$ }
- { * }
- if$
- "}]{" * write$
- cite$ write$
- "}" write$
- newline$
- ""
- before.all 'output.state :=
-}
-
-FUNCTION {n.dashify}
-{
- 't :=
- ""
- { t empty$ not }
- { t #1 #1 substring$ "-" =
- { t #1 #2 substring$ "--" = not
- { "--" *
- t #2 global.max$ substring$ 't :=
- }
- { { t #1 #1 substring$ "-" = }
- { "-" *
- t #2 global.max$ substring$ 't :=
- }
- while$
- }
- if$
- }
- { t #1 #1 substring$ *
- t #2 global.max$ substring$ 't :=
- }
- if$
- }
- while$
-}
-
-FUNCTION {word.in}
-{ bbl.in
- " " * }
-
-FUNCTION {format.date}
-{ year duplicate$ empty$
- { "empty year in " cite$ * "; set to ????" * warning$
- pop$ "????" }
- 'skip$
- if$
- extra.label *
- before.all 'output.state :=
- " (" swap$ * ")" *
-}
-
-FUNCTION {format.btitle}
-{ title emphasize
-}
-
-FUNCTION {tie.or.space.connect}
-{ duplicate$ text.length$ #3 <
- { "~" }
- { " " }
- if$
- swap$ * *
-}
-
-FUNCTION {either.or.check}
-{ empty$
- 'pop$
- { "can't use both " swap$ * " fields in " * cite$ * warning$ }
- if$
-}
-
-FUNCTION {format.bvolume}
-{ volume empty$
- { "" }
- { bbl.volume volume tie.or.space.connect
- series empty$
- 'skip$
- { bbl.of space.word * series emphasize * }
- if$
- "volume and number" number either.or.check
- }
- if$
-}
-
-FUNCTION {format.number.series}
-{ volume empty$
- { number empty$
- { series field.or.null }
- { output.state mid.sentence =
- { bbl.number }
- { bbl.number capitalize }
- if$
- number tie.or.space.connect
- series empty$
- { "there's a number but no series in " cite$ * warning$ }
- { bbl.in space.word * series * }
- if$
- }
- if$
- }
- { "" }
- if$
-}
-
-FUNCTION {is.num}
-{ chr.to.int$
- duplicate$ "0" chr.to.int$ < not
- swap$ "9" chr.to.int$ > not and
-}
-
-FUNCTION {extract.num}
-{ duplicate$ 't :=
- "" 's :=
- { t empty$ not }
- { t #1 #1 substring$
- t #2 global.max$ substring$ 't :=
- duplicate$ is.num
- { s swap$ * 's := }
- { pop$ "" 't := }
- if$
- }
- while$
- s empty$
- 'skip$
- { pop$ s }
- if$
-}
-
-FUNCTION {convert.edition}
-{ edition extract.num "l" change.case$ 's :=
- s "first" = s "1" = or
- { bbl.first 't := }
- { s "second" = s "2" = or
- { bbl.second 't := }
- { s "third" = s "3" = or
- { bbl.third 't := }
- { s "fourth" = s "4" = or
- { bbl.fourth 't := }
- { s "fifth" = s "5" = or
- { bbl.fifth 't := }
- { s #1 #1 substring$ is.num
- { s eng.ord 't := }
- { edition 't := }
- if$
- }
- if$
- }
- if$
- }
- if$
- }
- if$
- }
- if$
- t
-}
-
-FUNCTION {format.edition}
-{ edition empty$
- { "" }
- { output.state mid.sentence =
- { convert.edition "l" change.case$ " " * bbl.edition * }
- { convert.edition "t" change.case$ " " * bbl.edition * }
- if$
- }
- if$
-}
-
-INTEGERS { multiresult }
-
-FUNCTION {multi.page.check}
-{ 't :=
- #0 'multiresult :=
- { multiresult not
- t empty$ not
- and
- }
- { t #1 #1 substring$
- duplicate$ "-" =
- swap$ duplicate$ "," =
- swap$ "+" =
- or or
- { #1 'multiresult := }
- { t #2 global.max$ substring$ 't := }
- if$
- }
- while$
- multiresult
-}
-
-FUNCTION {format.pages}
-{ pages empty$
- { "" }
- { pages multi.page.check
- { bbl.pages pages n.dashify tie.or.space.connect }
- { bbl.page pages tie.or.space.connect }
- if$
- }
- if$
-}
-
-FUNCTION {format.journal.pages}
-{ pages empty$
- 'skip$
- { duplicate$ empty$
- { pop$ format.pages }
- {
- ", " *
- pages n.dashify *
- }
- if$
- }
- if$
-}
-
-FUNCTION {format.vol.num.pages}
-{ volume field.or.null
-}
-
-FUNCTION {format.chapter.pages}
-{ chapter empty$
- { "" }
- { type empty$
- { bbl.chapter }
- { type "l" change.case$ }
- if$
- chapter tie.or.space.connect
- }
- if$
-}
-
-FUNCTION {format.in.ed.booktitle}
-{ booktitle empty$
- { "" }
- { editor empty$
- { word.in booktitle emphasize * }
- { word.in booktitle emphasize *
- ", " *
- editor num.names$ #1 >
- { bbl.editors }
- { bbl.editor }
- if$
- * " " *
- format.in.editors *
- }
- if$
- }
- if$
-}
-
-FUNCTION {format.thesis.type}
-{ type empty$
- 'skip$
- { pop$
- type "t" change.case$
- }
- if$
-}
-
-FUNCTION {format.tr.number}
-{ type empty$
- { bbl.techrep }
- 'type
- if$
- number empty$
- { "t" change.case$ }
- { number tie.or.space.connect }
- if$
-}
-
-FUNCTION {format.article.crossref}
-{
- word.in
- " \cite{" * crossref * "}" *
-}
-
-FUNCTION {format.book.crossref}
-{ volume empty$
- { "empty volume in " cite$ * "'s crossref of " * crossref * warning$
- word.in
- }
- { bbl.volume volume tie.or.space.connect
- bbl.of space.word *
- }
- if$
- " \cite{" * crossref * "}" *
-}
-
-FUNCTION {format.incoll.inproc.crossref}
-{
- word.in
- " \cite{" * crossref * "}" *
-}
-
-FUNCTION {format.publisher}
-{ publisher empty$
- { "empty publisher in " cite$ * warning$ }
- 'skip$
- if$
- ""
- address empty$ publisher empty$ and
- 'skip$
- {
- address empty$
- 'skip$
- { address * }
- if$
- publisher empty$
- 'skip$
- { address empty$
- 'skip$
- { ": " * }
- if$
- publisher *
- }
- if$
- }
- if$
- output
-}
-
-STRINGS {oldname}
-
-FUNCTION {name.or.dash}
-{ 's :=
- oldname empty$
- { s 'oldname := s }
- { s oldname =
- { "---" }
- { s 'oldname := s }
- if$
- }
- if$
-}
-
-FUNCTION {article}
-{ output.bibitem
- format.authors "author" output.check
- author format.key output
- name.or.dash
- format.date "year" output.check
- date.block
- format.title "title" output.check
- end.quote.title
- crossref missing$
- { journal
- emphasize
- "journal" output.check
- format.vol.num.pages output
- }
- { format.article.crossref output.nonnull
- format.pages output
- }
- if$
- format.journal.pages
- format.note output
- fin.entry
-}
-
-FUNCTION {book}
-{ output.bibitem
- author empty$
- { format.editors "author and editor" output.check
- editor format.key output
- name.or.dash
- }
- { format.authors output.nonnull
- name.or.dash
- crossref missing$
- { "author and editor" editor either.or.check }
- 'skip$
- if$
- }
- if$
- format.date "year" output.check
- date.block
- format.btitle "title" output.check
- crossref missing$
- { format.bvolume output
- format.number.series output
- format.publisher
- }
- {
- format.book.crossref output.nonnull
- }
- if$
- format.edition output
- format.note output
- fin.entry
-}
-
-FUNCTION {booklet}
-{ output.bibitem
- format.authors output
- author format.key output
- name.or.dash
- format.date "year" output.check
- date.block
- format.title "title" output.check
- end.quote.title
- howpublished output
- address output
- format.note output
- fin.entry
-}
-
-FUNCTION {inbook}
-{ output.bibitem
- author empty$
- { format.editors "author and editor" output.check
- editor format.key output
- name.or.dash
- }
- { format.authors output.nonnull
- name.or.dash
- crossref missing$
- { "author and editor" editor either.or.check }
- 'skip$
- if$
- }
- if$
- format.date "year" output.check
- date.block
- format.btitle "title" output.check
- crossref missing$
- {
- format.publisher
- format.bvolume output
- format.chapter.pages "chapter and pages" output.check
- format.number.series output
- }
- {
- format.chapter.pages "chapter and pages" output.check
- format.book.crossref output.nonnull
- }
- if$
- format.edition output
- format.pages "pages" output.check
- format.note output
- fin.entry
-}
-
-FUNCTION {incollection}
-{ output.bibitem
- format.authors "author" output.check
- author format.key output
- name.or.dash
- format.date "year" output.check
- date.block
- format.title "title" output.check
- end.quote.title
- crossref missing$
- { format.in.ed.booktitle "booktitle" output.check
- format.publisher
- format.bvolume output
- format.number.series output
- format.chapter.pages output
- format.edition output
- }
- { format.incoll.inproc.crossref output.nonnull
- format.chapter.pages output
- }
- if$
- format.pages "pages" output.check
- format.note output
- fin.entry
-}
-
-FUNCTION {inproceedings}
-{ output.bibitem
- format.authors "author" output.check
- author format.key output
- name.or.dash
- format.date "year" output.check
- date.block
- format.title "title" output.check
- end.quote.title
- crossref missing$
- { format.in.ed.booktitle "booktitle" output.check
- publisher empty$
- { organization output
- address output
- }
- { organization output
- format.publisher
- }
- if$
- format.bvolume output
- format.number.series output
- format.pages output
- }
- { format.incoll.inproc.crossref output.nonnull
- format.pages output
- }
- if$
- format.note output
- fin.entry
-}
-
-FUNCTION {conference} { inproceedings }
-
-FUNCTION {manual}
-{ output.bibitem
- format.authors output
- author format.key output
- name.or.dash
- format.date "year" output.check
- date.block
- format.btitle "title" output.check
- organization output
- address output
- format.edition output
- format.note output
- fin.entry
-}
-
-FUNCTION {mastersthesis}
-{ output.bibitem
- format.authors "author" output.check
- author format.key output
- name.or.dash
- format.date "year" output.check
- date.block
- format.title "title" output.check
- end.quote.title
- bbl.mthesis format.thesis.type output.nonnull
- school "school" output.check
- address output
- format.note output
- fin.entry
-}
-
-FUNCTION {misc}
-{ output.bibitem
- format.authors output
- author format.key output
- name.or.dash
- format.date "year" output.check
- date.block
- format.title output
- end.quote.title
- howpublished output
- format.note output
- fin.entry
-}
-
-FUNCTION {phdthesis}
-{ output.bibitem
- format.authors "author" output.check
- author format.key output
- name.or.dash
- format.date "year" output.check
- date.block
- format.title "title" output.check
- end.quote.title
- bbl.phdthesis format.thesis.type output.nonnull
- school "school" output.check
- address output
- format.note output
- fin.entry
-}
-
-FUNCTION {proceedings}
-{ output.bibitem
- format.editors output
- editor format.key output
- name.or.dash
- format.date "year" output.check
- date.block
- format.btitle "title" output.check
- format.bvolume output
- format.number.series output
- address output
- organization output
- publisher output
- format.note output
- fin.entry
-}
-
-FUNCTION {techreport}
-{ output.bibitem
- format.authors "author" output.check
- author format.key output
- name.or.dash
- format.date "year" output.check
- date.block
- format.title "title" output.check
- end.quote.title
- format.tr.number output.nonnull
- institution "institution" output.check
- address output
- format.note output
- fin.entry
-}
-
-FUNCTION {unpublished}
-{ output.bibitem
- format.authors "author" output.check
- author format.key output
- name.or.dash
- format.date "year" output.check
- date.block
- format.title "title" output.check
- end.quote.title
- format.note "note" output.check
- fin.entry
-}
-
-FUNCTION {default.type} { misc }
-
-READ
-
-FUNCTION {sortify}
-{ purify$
- "l" change.case$
-}
-
-INTEGERS { len }
-
-FUNCTION {chop.word}
-{ 's :=
- 'len :=
- s #1 len substring$ =
- { s len #1 + global.max$ substring$ }
- 's
- if$
-}
-
-FUNCTION {format.lab.names}
-{ 's :=
- s #1 "{vv~}{ll}" format.name$
- s num.names$ duplicate$
- #2 >
- { pop$
- " et~al." *
- }
- { #2 <
- 'skip$
- { s #2 "{ff }{vv }{ll}{ jj}" format.name$ "others" =
- {
- " et~al." *
- }
- { bbl.and space.word * s #2 "{vv~}{ll}" format.name$
- * }
- if$
- }
- if$
- }
- if$
-}
-
-FUNCTION {author.key.label}
-{ author empty$
- { key empty$
- { cite$ #1 #3 substring$ }
- 'key
- if$
- }
- { author format.lab.names }
- if$
-}
-
-FUNCTION {author.editor.key.label}
-{ author empty$
- { editor empty$
- { key empty$
- { cite$ #1 #3 substring$ }
- 'key
- if$
- }
- { editor format.lab.names }
- if$
- }
- { author format.lab.names }
- if$
-}
-
-FUNCTION {editor.key.label}
-{ editor empty$
- { key empty$
- { cite$ #1 #3 substring$ }
- 'key
- if$
- }
- { editor format.lab.names }
- if$
-}
-
-FUNCTION {calc.short.authors}
-{ type$ "book" =
- type$ "inbook" =
- or
- 'author.editor.key.label
- { type$ "proceedings" =
- 'editor.key.label
- 'author.key.label
- if$
- }
- if$
- 'short.list :=
-}
-
-FUNCTION {calc.label}
-{ calc.short.authors
- short.list
- "("
- *
- year duplicate$ empty$
- { pop$ "????" }
- 'skip$
- if$
- *
- 'label :=
-}
-
-FUNCTION {sort.format.names}
-{ 's :=
- #1 'nameptr :=
- ""
- s num.names$ 'numnames :=
- numnames 'namesleft :=
- { namesleft #0 > }
- { s nameptr
- "{vv{ } }{ll{ }}{ f{ }}{ jj{ }}"
- format.name$ 't :=
- nameptr #1 >
- {
- " " *
- namesleft #1 = t "others" = and
- { "zzzzz" * }
- { t sortify * }
- if$
- }
- { t sortify * }
- if$
- nameptr #1 + 'nameptr :=
- namesleft #1 - 'namesleft :=
- }
- while$
-}
-
-FUNCTION {sort.format.title}
-{ 't :=
- "A " #2
- "An " #3
- "The " #4 t chop.word
- chop.word
- chop.word
- sortify
- #1 global.max$ substring$
-}
-
-FUNCTION {author.sort}
-{ author empty$
- { key empty$
- { "to sort, need author or key in " cite$ * warning$
- ""
- }
- { key sortify }
- if$
- }
- { author sort.format.names }
- if$
-}
-
-FUNCTION {author.editor.sort}
-{ author empty$
- { editor empty$
- { key empty$
- { "to sort, need author, editor, or key in " cite$ * warning$
- ""
- }
- { key sortify }
- if$
- }
- { editor sort.format.names }
- if$
- }
- { author sort.format.names }
- if$
-}
-
-FUNCTION {editor.sort}
-{ editor empty$
- { key empty$
- { "to sort, need editor or key in " cite$ * warning$
- ""
- }
- { key sortify }
- if$
- }
- { editor sort.format.names }
- if$
-}
-
-FUNCTION {presort}
-{ calc.label
- label sortify
- " "
- *
- type$ "book" =
- type$ "inbook" =
- or
- 'author.editor.sort
- { type$ "proceedings" =
- 'editor.sort
- 'author.sort
- if$
- }
- if$
- #1 entry.max$ substring$
- 'sort.label :=
- sort.label
- *
- " "
- *
- title field.or.null
- sort.format.title
- *
- #1 entry.max$ substring$
- 'sort.key$ :=
-}
-
-ITERATE {presort}
-
-SORT
-
-STRINGS { last.label next.extra }
-
-INTEGERS { last.extra.num number.label }
-
-FUNCTION {initialize.extra.label.stuff}
-{ #0 int.to.chr$ 'last.label :=
- "" 'next.extra :=
- #0 'last.extra.num :=
- #0 'number.label :=
-}
-
-FUNCTION {forward.pass}
-{ last.label label =
- { last.extra.num #1 + 'last.extra.num :=
- last.extra.num int.to.chr$ 'extra.label :=
- }
- { "a" chr.to.int$ 'last.extra.num :=
- "" 'extra.label :=
- label 'last.label :=
- }
- if$
- number.label #1 + 'number.label :=
-}
-
-FUNCTION {reverse.pass}
-{ next.extra "b" =
- { "a" 'extra.label := }
- 'skip$
- if$
- extra.label 'next.extra :=
- extra.label
- duplicate$ empty$
- 'skip$
- { "{\natexlab{" swap$ * "}}" * }
- if$
- 'extra.label :=
- label extra.label * 'label :=
-}
-
-EXECUTE {initialize.extra.label.stuff}
-
-ITERATE {forward.pass}
-
-REVERSE {reverse.pass}
-
-FUNCTION {bib.sort.order}
-{ sort.label
- " "
- *
- year field.or.null sortify
- *
- " "
- *
- title field.or.null
- sort.format.title
- *
- #1 entry.max$ substring$
- 'sort.key$ :=
-}
-
-ITERATE {bib.sort.order}
-
-SORT
-
-FUNCTION {begin.bib}
-{ preamble$ empty$
- 'skip$
- { preamble$ write$ newline$ }
- if$
- "\begin{thebibliography}{" number.label int.to.str$ * "}" *
- write$ newline$
- "\newcommand{\enquote}[1]{``#1''}"
- write$ newline$
- "\expandafter\ifx\csname natexlab\endcsname\relax\def\natexlab#1{#1}\fi"
- write$ newline$
-}
-
-EXECUTE {begin.bib}
-
-EXECUTE {init.state.consts}
-
-ITERATE {call.type$}
-
-FUNCTION {end.bib}
-{ newline$
- "\end{thebibliography}" write$ newline$
-}
-
-EXECUTE {end.bib}
-%% End of customized bst file
-%%
-%% End of file `asa.bst'.
diff --git a/vignettes/balance.tex b/vignettes/balance.tex
deleted file mode 100644
index 15515cf..0000000
--- a/vignettes/balance.tex
+++ /dev/null
@@ -1,135 +0,0 @@
-\section{Checking Balance}
-\label{sec:balance}
-
-\subsection{Quick Overview}
-
-To check balance, use \texttt{summary(m.out)} for numerical summaries
-and \texttt{plot(m.out)} for graphical summaries.
-
-\subsection{Details}
-
-\subsubsection{The {\tt summary()} Command}
-
-The \texttt{summary()} command gives measures of the balance between
-the treated and control groups in the full (original) data set, and
-then in the matched data set. If the matching worked well, the
-measures of balance should be smaller in the matched data set (smaller
-values of the measures indicate better balance).
-
-The \texttt{summary()} output for subclassification is the same as
-that for other types of matching, except that the balance statistics
-are shown separately for each subclass, and the overall balance in the
-matched samples is calculated by aggregating across the subclasses,
-where each subclass is weighted by the number of units in the
-subclass. For exact matching, the covariate values within each
-subclass are guaranteed to be the same, and so the measures of balance
-are not output for exact matching; only the sample sizes in each
-subclass are shown.
-
-\begin{itemize}
-\item {\bf Balance statistics:} The statistics the \texttt{summary()}
- command provides include means, the original control group standard deviation (where applicable),
- mean differences, standardized mean
- differences, and (median, mean and maximum) Quantile-Quantile (Q-Q)
- plot differences. In addition, the \texttt{summary()} command will
- report (a) the matched call, (b) how many units were matched,
- unmatched, or discarded due to the \texttt{discard} option
- (described below), and (c) the percent improvement in balance for
- each of the balance measures, defined as $100((|a|-|b|)/|a|)$, where
- $a$ is the balance before and $b$ is the balance after matching.
- For each set of units (original and matched data sets, with weights
- used as appropriate in the matched data sets), the
- following statistics are provided:
-\begin{enumerate}
- \item ``Means Treated'' and ``Means Control'' show the weighted
- means in the treated and control groups
- \item ``SD Control" is the standard deviation calculated in the control group (where applicable)
- \item ``Mean Diff'' is the difference in means between the groups
- \item The final three columns of the summary output give summary
- statistics of a Q-Q plot (see below for more information on these
- plots). Those columns give the median, mean, and maximum distance
- between the two empirical quantile functions (treated and control
- groups). Values greater than 0 indicate deviations between the
- groups in some part of the empirical distributions. The plots of
- the two empirical quantile functions themselves, described below,
- can provide further insight into which part of the covariate
- distribution has differences between the two groups.
-\end{enumerate}
-
-\item {\bf Additional options:} Three options to the \texttt{summary()}
- command can also help with assessing balance and respecifying the
- propensity score model, as necessary. First, the {\tt interactions
- = TRUE} option with {\tt summary()} shows the balance of all
- squares and interactions of the covariates used in the matching
- procedure. Large differences in higher order interactions usually
- are a good indication that the propensity score model (the distance measure) needs to be
- respecified. Similarly, the {\tt addlvariables} option with {\tt
- summary()} will provide balance measures on additional variables
- not included in the original matching procedure. If a variable (or
- interaction of variables) not included in the original propensity score model
- has large imbalances in the matched groups, including that
- variable in the next model specification may improve the resulting
- balance on that variable. Because the outcome variable is not used
- in the matching procedure, a variety of matching methods can be
- tried, and the one that leads to the best resulting balance chosen. Finally,
- the {\tt standardize = TRUE} option will print out standardized versions of the
- balance measures, where the mean difference is standardized (divided) by the standard deviation
- in the original treated group.
-\end{itemize}
-
-\subsubsection{The \texttt{plot()} Command}
-
-We can also examine the balance graphically using the \texttt{plot()}
-command, which provides three types of plots: jitter plots of the
-distance measure, Q-Q plots of each covariate, and histograms of the
-distance measure. For subclassification, separate Q-Q plots can be
-printed for each subclass. The jitter plot for subclassification is
-the same as that for other types of matching, with the addition of
-vertical lines indicating the subclass cut-points. With the histogram
-option, 4 histograms are provided: the original treated and control
-groups and the matched treated and control groups. For the Q-Q plots
-and the histograms, the weights that result after matching are used to
-create the plots.
-
-Three examples of the output from the {\tt plot()} command are shown
-in Figure~\ref{fig:plotcommandoutput}. If the empirical distributions
-are the same in the treated and control groups, the points in the Q-Q
-plots would all lie on the 45 degree line (lower left panel of
-Figure~\ref{fig:plotcommandoutput}). Deviations from the 45 degree
-line indicate differences in the empirical distribution. The jitter
-plot (top panel) shows the overall distribution of propensity scores
-in the treated and control groups. In the jitter plot, which can be
-created by setting \texttt{type = "jitter"}, the size of each point is
-proportional to the weight given to that unit. Observation names can
-be interactively identified by clicking the first mouse button near
-the units. The histograms (lower right panel) can be plotted by
-setting \texttt{type = "hist"}.
-
-\begin{figure}
- \begin{center}
- \includegraphics[height=2.7in, keepaspectratio=true]{figs/jitterplotnn.pdf}
- \includegraphics[height=3in,keepaspectratio=true]{figs/qqplotnn1.pdf}
- \includegraphics[height=3in,keepaspectratio=true]{figs/hist.pdf}
- \caption{Examples of the three types of output from the
- \texttt{plot} command resulting from matching on the
- /texttt{lalonde} data set based on real earnings in 1974
- (\texttt{re74}) divided by 1000, real earnings in 1975
- (\texttt{re75}) divided by 1000, years of education
- (\texttt{educ}), Hispanic (\texttt{hispan}) and marital status
- (\texttt{married}). Observations in both the treated and the
- control groups outside the support of the distance measure were
- discarded. The upper plot shows the jitter plot of the distance
- measure. The lower left plot shows the QQ plots for the first
- three covariates (\texttt{I(re74/1000)}, \texttt{I(re75/1000)},
- \texttt{educ}). The lower right plot shows the histograms of the
- density of propensity scores for observations before and after
- matching.}
- \label{fig:plotcommandoutput}
-\end{center}
-\end{figure}
-
-
-%%% Local Variables:
-%%% mode: latex
-%%% TeX-master: "matchit"
-%%% End:
diff --git a/vignettes/dcolumn.sty b/vignettes/dcolumn.sty
deleted file mode 100644
index f0a413a..0000000
--- a/vignettes/dcolumn.sty
+++ /dev/null
@@ -1,91 +0,0 @@
-%%
-%% This is file `dcolumn.sty', generated
-%% on <1992/10/29> with the docstrip utility (2.0r).
-%%
-%% The original source files were:
-%%
-%% dcolumn.doc (with options: `style')
-%%
-%% This file is part of the array package.
-%% ---------------------------------------
-%%
-%% It is a contributed file.
-%% In case of errors please inform the original author.
-%%
-%% The checksum in the header refers to the documented version of
-%% the file.
-%%
-
-
-%%% ====================================================================
-%%% @LaTeX-style-file{
-%%% author = "David Carlisle",
-%%% version = "1.01",
-%%% date = "12 June 1992",
-%%% time = "16:24:45 BST",
-%%% filename = "dcolumn.sty",
-%%% address = "Computer Science Department
-%%% Manchester University
-%%% Oxford Road
-%%% Manchester
-%%% England
-%%% M13 9PL",
-%%% telephone = "+44 61 275 6139",
-%%% FAX = "+44 61 275 6236",
-%%% checksum = "48012 272 1205 9538",
-%%% email = "carlisle at cs.man.ac.uk (Internet)",
-%%% codetable = "ISO/ASCII",
-%%% keywords = "LaTeX, tabular, array, decimal",
-%%% supported = "yes",
-%%% docstring = "
-%%%
-%%% dcolumn.sty
-%%%
-%%% A LaTeX style option for producing tabular entries aligned on a
-%%% decimal point.
-%%% The `decimal point' may be any math-mode material, or just `.'.
-%%%
-%%% Requires array.sty.
-%%% Documentation requires Mittelbach's doc.sty.
-%%%
-%%% The checksum field above was produced by
-%%% Robert Solovay's checksum utility.",
-%%% }
-%%% ====================================================================
-\def\fileversion{v1.01}
-\def\filedate{92/06/12}
-\def\docdate {92/06/17}
-\@ifundefined{DC at centre}{}{\endinput}
-\wlog{Style-Option: `dcolumn' \fileversion
- \space\space <\filedate> (D.P.C.)}
-\wlog{English documentation dated \space <\docdate> (D.P.C.)}
-\@ifundefined{newcolumntype}{\input array.sty}{}
-\def\DC@#1#2#3{%
- \uccode`\~=`#1\relax
- \m at th
- \ifnum #3 < \z@ \expandafter\DC at centre
- \else \expandafter\DC at right \fi
- {#1}{#2}{#3}}
-\def\DC at centre#1#2#3{%
- \let\DC at end\DC at endcentre
- \uppercase{\def~}{$\egroup\setbox\tw@=\hbox\bgroup${#2}}%
- \setbox\tw@=\hbox{${\phantom{{#2}}}$}%
- \setbox\z@=\hbox\bgroup$\mathcode`#1="8000 }
-\def\DC at endcentre{$\egroup
- \ifdim \wd\z@>\wd\tw@
- \setbox\tw@=\hbox to\wd\z@{\unhbox\tw@\hfill}%
- \else
- \setbox\z@=\hbox to\wd\tw@{\hfill\unhbox\z@}\fi
- \box\z@\box\tw@}
-\def\DC at right#1#2#3{%
- \let\DC at end\DC at endright
- \uppercase{\def~}{$\egroup\setbox\tw@=\hbox to \dimen@\bgroup${#2}}%
- \setbox\z@=\hbox{$1$}\dimen@=#3\wd\z@
- \setbox\z@=\hbox{${#2}$}\advance\dimen@\wd\z@
- \setbox\tw@=\hbox to \dimen@{}%
- \setbox\z@=\hbox\bgroup$\mathcode`#1="8000 }
-\def\DC at endright{$\hfil\egroup\hfill\box\z@\box\tw@}
-\newcolumntype{D}[3]{>{\DC@{#1}{#2}{#3}}c<{\DC at end}}
-\endinput
-%%
-%% End of file `dcolumn.sty'.
diff --git a/vignettes/face_off.jpg b/vignettes/face_off.jpg
deleted file mode 100644
index 8cf9060..0000000
Binary files a/vignettes/face_off.jpg and /dev/null differ
diff --git a/vignettes/faq.tex b/vignettes/faq.tex
deleted file mode 100644
index 2202806..0000000
--- a/vignettes/faq.tex
+++ /dev/null
@@ -1,194 +0,0 @@
-\chapter{Frequently Asked Questions}
-
-\section{How do I Cite this Work?}
-
-If you use \MatchIt, please cite\nocite{HoImaKin07,HoImaKin07a}
-\begin{verse}
- Daniel Ho; Kosuke Imai; Gary King; and Elizabeth Stuart (2007),
- ``Matching as Nonparametric Preprocessing for Reducing Model
- Dependence in Parametric Causal Inference,'' \emph{Political
- Analysis} 15(3): 199-236,
- \url{http://gking.harvard.edu/files/abs/matchp-abs.shtml}.
-
-and
-
-Daniel Ho; Kosuke Imai; Gary King; and Elizabeth Stuart (2007b)
-``Matchit: Nonparametric Preprocessing for Parametric Causal
-Inference,'' \emph{Journal of Statistical Software},
-\url{http://gking.harvard.edu/matchit/}.
-\end{verse}
-
-In addition, the {\tt convex.hull} discard option is implemented via
-the {\tt WhatIf} package \citep{KinZen06,KinZen07,StoKinZen05}.
-Generalized linear distance measures are implemented via the {\tt
- stats} package \citep{VenRip02}. Generalized additive distance
-measures are implemented via the {\tt mcgv} package \citep{HasTib90}.
-The neural network distance measure is implemented via the {\tt nnet}
-package \citep{Ripley96}. The classification trees distance measure
-is implemented via the {\tt rpart} package \citep{BreFriOls84}. Full
-and optimal matching are implemented via the {\tt optmatch} package
-\citep{Hansen04}. Genetic matching is implemented via the {\tt
- Matching} package \citep{DiaSek05}. Coarsened exact matching is
-implemented via the \texttt{cem} package
-\citep{IacKinPor08,IacKinPor08b}.
-
-\section{What if My datasets Are Big and Are Taking Up
- Too Much Memory?}
-
-{\tt matchit()} does not save the data set in its output object, but
-it does save a matrix of the covariates. {\tt match.data()} will
-create a matched data set. One can eliminate the original data set to
-save memory in R by {\tt rm(name)}, where {\tt name} is the name of
-the data set, after calling {\tt match.data()}.
-
-%\section{Can I use a Difference-in-Difference Estimator for Matched
-% Data?}
-%
-%A difference-in-differences (DID) analysis can be easily conducted
-%with \MatchIt. If we were interested in the DID matching estimate in
-%the Lalonde data, we could simply include {\texttt re75} as a
-%covariate in the preprocessing step. Then the analysis can be
-%performed on the change in income from 1975 to 1978: {\tt re78}-{\tt
-% re75}. Time-varying covariates (of which none exist in the Lalonde
-%data) should of course also be differenced for the DID estimator.
-%** we should show how to do this with zelig
-
-\section{How Exactly are the Weights Created?}
-\label{subsec:weights}
-
-Each type of matching method can be thought of as creating groups of
-units with at least one treated unit and at least one control unit in
-each. In exact matching, subclassification, or full matching, these
-groups are the subclasses formed, and the number of treated and
-control units will vary quite a bit across subclasses. In nearest
-neighbor or optimal matching, the groups are the pairs (or sets) of
-treated and control units matched. In 1:1 nearest neighbor matching
-there will be one treated unit and one control unit in each group. In
-2:1 nearest neighbor matching there will be one treated unit and two
-control units in each group. Unmatched units receive a weight of 0.
-All matched treated units receive a weight of 1. These weights are constructed
-to estimate the average treatment effect on the treated, with the control group
-essentially weighted to look like the treated group.
-
-The weights for matched control units are formed as follows:
-\begin{enumerate}
-\item Within each group, each control unit is given a preliminary
- weight of $n_{ti}/n_{ci}$, where $n_{ti}$ and $n_{ci}$ are the
- number of treated and control units in group $i$, respectively.
-\item If matching is done with replacement, each control unit's weight
- is added up across the groups in which it was matched.
-\item The control group weights are scaled to sum to the number of
- uniquely matched control units.
-\end{enumerate}
-
-With subclassification, when the analysis is done separately within
-each subclass and then aggregated up across the subclasses, these
-weights will generally not be used, but they may be used for full
-matching or nearest neighbor matching if the number of control units
-matched to each treated unit varies.
-
-
-
-\section{How Do I Create Observation Names?}
-\label{rnames}
-
-Since the diagnostics often make use of the observation names of the
-data frame, you may find it helpful to specify observation names for
-the data input. Use the \texttt{row.names} command to achieve this.
-For example, to assign the names ``Dan'', ``Kosuke'', ``Liz'' and
-``Gary'' to a data frame with the first four observations in the
-Lalonde data, type:
-
-
-\begin{verbatim}
-> test <- lalonde[1:4, ]
-> row.names(test) <- c("Dan", "Kosuke", "Liz", "Gary")
-> print(test)
- age educ black hisp married nodegr re74 re75 re78 u74 u75 treat
-Dan 37 11 1 0 1 1 0 0 9930 1 1 1
-Kosuke 22 9 0 1 0 1 0 0 3596 1 1 1
-Liz 30 12 1 0 0 0 0 0 24910 1 1 1
-Gary 27 11 1 0 0 1 0 0 7506 1 1 1
-\end{verbatim}
-
-\section{How Can I See Outcomes of Matched Pairs?}
-
-To obtain outcomes of matched pairs, recall that the original dataset has unique row names corresponding to each of
-the observations. The row names of \texttt{match.matrix} correspond to the names of the treated, and each
-of the cells corresponds to a name of matched controls. So to obtain matched outcomes, you can use:
-
-\begin{verbatim}
-cbind(lalonde[row.names(foo$match.matrix),"re78"], lalonde[foo$match.matrix,"re78"])
-\end{verbatim}
-
-\section{How Do I Ensure Replicability As \MatchIt\ Versions Develop?}
-\label{subsec:vercontrol}
-
-As the literature on matching techniques is rapidly evolving,
-\MatchIt\ will strive to incorporate new developments. \MatchIt\ is
-thereby an evolving program. Users may be concerned that analysis
-written in a particular version may not be compatible with newer
-versions of the program. The primary way to ensure that replication
-archives remain valid is to record the version of \MatchIt\ that was
-used in the analysis. Our website maintains binaries of all public
-release versions, so that researchers can replicate results exactly
-with the appropriate version (for Unix-based platforms, see
-\hlink{http://gking.harvard.edu/src/contrib/}{http://gking.harvard.edu/src/contrib/};
-for windows, see
-\hlink{http://gking.harvard.edu/bin/windows/contrib/}{http://gking.harvard.edu/bin/windows/contrib/}).
-
-In addition, users may find it helpful to install packages with
-version control, using the {\tt installWithVers} command with {\tt
-install.packages}. So for example, in the windows R console, users
-may download the appropriate version from our website and install the
-package with version control by:
-
-\begin{verbatim}
-install.packages(choose.files('',filters=Filters[c('zip','All'),]),
- .libPaths()[1],installWithVers=T,CRAN=NULL)
-\end{verbatim}
-
-{\tt R CMD INSTALL} similarly permits users to specify this version
-using the \\ {\tt --with-package-versions} option. After having
-specified version control, different versions of the program may be
-called as necessary. Similar advice may also be appropriate for
-version control for R more generally.
-
-\section{How Do I Use My Own Distance Measure with \MatchIt\,?}
-
-A vector of your own distance measure can be used by specifying it as
-the input for {\tt distance} option in {\tt matchit()}.
-
-\section{What Do I Do about Missing Data?}
-
-\MatchIt\ requires complete data sets, with no missing values (other
-than potential outcomes of course). If there are missing values in
-the data set, imputation techniques should be used first to fill in
-(``impute'') the missing values (both covariates and outcomes), or the
-analysis should be done using only complete cases (which we do not in
-general recommend). For imputation software, see Amelia at
-(\hlink{http://gking.harvard.edu/stats.shtml}{http://gking.harvard.edu/stats.shtml})
-or other programs at
-\hlink{http://www.multiple-imputation.com}{http://www.multiple-imputation.com}.
-For more information on missing data and imputation methods, see
-\cite{KinHonJos01}.
-
-\section{Why Preprocessing?}
-
-The purpose of matching is to approximate an experimental template,
-where the matching procedure approximates blocking prior to random
-treatment assignment in order to balance covariates between treatment
-and control groups. Separation of the estimation procedure into two
-steps simulates the research design of an experiment, where no
-information on outcomes is known at the point of experimental design
-and randomization. The separation of the balancing process in
-\MatchIt\ from the analysis process afterward helps keep clear the
-goal of balancing control and treatment groups and makes it less
-likely that the user will inadvertently cook the books in his or her
-favor.
-
-
-%%% Local Variables:
-%%% mode: latex
-%%% TeX-master: t
-%%% End:
diff --git a/vignettes/gk.bib b/vignettes/gk.bib
deleted file mode 100644
index 4443c0a..0000000
--- a/vignettes/gk.bib
+++ /dev/null
@@ -1,20380 +0,0 @@
-% A bibtex file for papers by or coauthored with Gary King
-%
-% To add references, first please CHECK that your doesn't already
-% exist in this file and
-% then add entries only at the end.
-%
-% Use these rules for the reference label:
-%
-% -if one author: use last name and last 2 digits of the year: Tobler79.
-% -if multiple authors, use 1st 3 letters of each of UP TO the first three
-% authors and the last 2 digits of the year: KinTomWit00.
-% -if necessary add lower-case letters for multiple entries in a year: King02, King02b
-% (the first one should NOT have an 'a' afterwards)
-%
-% -feel free to use the abbreviations at the start, or add to them.
-% -Use authors full names when known.
-%
-% please be sure to commit changes to CVS regularly as a number of
-% people are all using this at the same time.
-
- at STRING{ prq = "Political Research Quarterly"}
- at STRING{ apsr = "American Political Science Review"}
- at STRING{ ajps = "American Journal of Political Science"}
- at STRING{ jop = "Journal of Politics"}
- at STRING{ bjps = "British Journal of Political Science"}
- at STRING{ jleo = "Journal of Law, Economics, and Organization"}
- at STRING{ isa = "Paper presented at the annual meetings of the International Studies Association"}
- at STRING{ apsa = "Paper presented at the annual meetings of the American Political Science Association"}
- at STRING{ cp = "Comparative Politics"}
- at STRING{ io = "International Organization"}
- at STRING{ midwest = "Paper presented at the Annual Meeting of the Midwest Political Science Association"}
- at STRING{ mpsa = "midwest"}
- at STRING{ southern = "Paper presented at the Annual Meeting of the Southern Political Science Association"}
- at STRING{ icpsr = "Inter-University Consortium for Political and Social Research"}
- at STRING{ jasa = "Journal of the American Statistical Association"}
- at STRING{ lsq = "Legislative Studies Quarterly"}
- at STRING{ isq = "International Studies Quarterly"}
- at STRING{ tas = "The American Statistician"}
- at STRING{ jbes = "Journal of Business \& Economic Statistics"}
- at STRING{ joe = "Journal of Econometrics"}
- at STRING{ wp = "World Politics"}
- at STRING{ cup = "Cambridge University Press"}
- at STRING{ hup = "Harvard University Press"}
- at STRING{ ny = "New York"}
- at STRING{ sv = "Springer Verlag"}
- at STRING{ pup = "Princeton University Press"}
- at STRING{ ucp = "University of California Press"}
- at STRING{ ap = "Academic Press"}
- at STRING{ wb = "The World Bank"}
- at STRING{ eas = "Europe-Asia Studies"}
- at STRING{ jet = "Journal of Economic Theory"}
- at STRING{ jrssA = "Journal of the Royal Statistical Society, A"}
- at STRING{ jrssb = "Journal of the Royal Statistical Society, B"}
- at STRING{ poq = "Public Opinion Quarterly"}
- at STRING{ pnas = "Proceedings of the National Academy of Sciences"}
- at STRING{ ai = "Artificial Intelligence"}
- at STRING{ pa = "Political Analysis"}
- at STRING{ ps = "PS: Political Science and Politics"}
- at STRING{ smr = "Sociological Methods and Research"}
- at STRING{ sim = "Statistics in Medicine"}
- at STRING{ asr = "American Sociological Review"}
- at STRING{ bmj = "British Medical Journal"}
- at STRING{ lan = "Lancet"}
- at STRING{ dem = "Demography"}
- at STRING{ bull = "Bulletin of WHO"}
- at STRING{ ssm = "Social Science and Medicine"}
- at STRING{ mitai = "Artificial Intelligence Laboratory, Massachusetts Institute of Technology"}
- at STRING{ nc = "Neural Computation"}
-
- at article{AbaDruLeb02,
- author = {Alberto Abadie and David Druckker and Jane Leber
- Herr and Guido W. Imbens},
- title = {Implementing Matching Estimators for Average
- Treatment Effects in Stata},
- journal = {The Stata Journal},
- volume = 1,
- year = 2002,
- pages = {1--18},
- number = 1
-}
-
- at article{Bin83,
- author = {David A. Binder},
- title = {On the Variance of Asymptoticaly Normal Estimators from Complex Surveys},
- year = {1983},
- journal = {International Statistical Review},
- volume = {51},
- number = {3},
- pages = {279--292}
-}
-
- at article{HorTho52,
- author = {D. G. Horvitz and D.J. Thompson},
- title = {A Generalization of Sampling without Replacement
- from a Finite Universe},
- year = {1952},
- journal = {Journal of the American Statistical Association},
- volume = {47},
- pages = {663--685}
-}
-
- at article{AbaGelLev08,
- author = {Kobi Abayomi and Andrew Gelman and Marc Levy},
- title = {Diagnostics for Multivariate Imputations},
- journal = {Applied Statistics},
- volume = {57},
- number = {3},
- pages = {273--291},
- year = {2008}
-}
-
- at misc{AbaImb05,
- author = {Alberto Abadie and Guido Imbens},
- title = {Estimation of the Conditional Variance in Paired
- Experiments},
- year = 2006,
- howpublished = {KSG Working Paper},
- note =
- {{http://ksghome.harvard.edu/\~{}.aabadie.academic.ksg/cve.pdf}}
-}
-
-
- at misc{AbaImb09,
- author = {Alberto Abadie and Guido Imbens},
- title = {A Martingale Representation for Matching Estimators},
- year = 2009,
- howpublished = {IZA Discussion Papers number 4073},
- note = {{http://ftp.iza.org/dp4073.pdf}}
-}
-
-
-
- at article{Imb00,
- author = {Guido Imbens},
- title = {The role of the propensity score in estimating the dose-response functions},
- year = {2000},
- journal = {Biometrika},
- pages = {706--710},
- volume = {87},
- issue = {3}
-}
-
- at article{AbaImb07b,
- author = {Alberto Abadie and Guido Imbens},
- title = {On the Failure of the Bootstrap for Matching Estimators},
- year = {2007},
- journal = {Econometrica},
- pages = {1537--1557},
- volume = {76},
- issue = {6}
-}
-
- at article{AbaImb06,
- author = {Abadie, Alberto and Imbens, Guido W.},
- title = {Large Sample Properties of Matching Estimators for
- Average Treatment Effects},
- journal = {Econometrica},
- volume = {74},
- year = {2006},
- pages = {235--267},
- number = {1}
-}
-
- at inproceedings{Abu-Mostafa92,
- author={Y. Abu-Mostafa},
- title={A Method for Learning from Hints},
- booktitle={Advances in Neural information processings systems 5},
- year={1992},
- publisher={Morgan Kaufmann Publishers},
- address={San Mateo, CA},
- editor={S. J. Hanson and Jack D. Cowan and C. Lee Giles}
-}
-
- at article{Abu-Mostafa92,
- author={Y. Abu-Mostafa},
- title={A Method for Learning from Hints},
- journal={Advances in Neural information processings systems 5},
- volume={1992},
- pages={Morgan Kaufmann Publishers},
- month={San Mateo CA},
- number={S. J. Hanson and Jack D. Cowan and C. Lee Giles}
-}
-
- at book{Achen86,
- author={Christopher Achen},
- title={Statistical Analysis of Quasi-experiments},
- publisher={University of California Press},
- year={1986},
- address={Berkeley}
-}
-
- at techreport{AdaCoaRue00,
- author={Michelle Adato and David Coady and Marie Ruel},
- title={An Operations Evaluation of Progresa from the Perspective of Beneficiaries,
- Promotoras, School Directors and Health Staff},
- institution={International Food Policy Research Institute},
- year={2000},
- month={August},
- type={Final Report},
- address={2033 K Street, NW Washington, DC 20006}
-}
-
- at article{AdaGla05,
- author={Adamic, L.A. and Glance, N.},
- title={{The political blogosphere and the 2004 US election: divided they blog}},
- journal={Proceedings of the 3rd international workshop on Link discovery},
- year={2005},
- pages={36--43},
- publisher={ACM Press New York, NY, USA}
-}
-
- at article{AgoDyn04,
- author={Roberto Agodini and Mark Dynarski},
- title={Are experiments the only option? {A} look at dropout prevention programs},
- journal={Review of Economics and Statistics},
- volume= 86,
- year= 2004,
- pages={180-194},
- month={February},
- number= 1
-}
-
- at unpublished{AgrRajSri03,
- author={Rakesh Agrawal and Sridhar Rajagopolan and Ramakrishnan Srikant and Yirong
- Xu},
- title={Mining Newsgroups Using Networks Arising from Social Behavior},
- note={IBM ALmaden Research Center 650 Harry Rd., San Jose, CA 95120},
- year={2003},
- month={May}
-}
-
- at book{Aitchison86,
- author={J. Aitchison},
- title={The Statistical Analysis of Compositional Data},
- publisher={Chapman and Hall},
- year= 1986,
- address={London}
-}
-
- at article{Albert88,
- author={James H. Albert},
- title={Computational Methods Using a Bayesian Hierarchical Generalized Linear Model},
- journal={Journal of the American Statistical Association},
- volume={83},
- year={1988},
- pages={1037-1004},
- month={December},
- number={404}
-}
-
- at article{AldMcK77,
- author={John H. Aldrich and Richard D. McKelvey},
- title={A Method of Scaling With Applications to the 1968 and 1972 Presidential
- Elections},
- journal= apsr,
- volume= 71,
- year= 1977,
- pages={111-130},
- month={March}
-}
-
- at article{AleTab90,
- author={Alberto Alesina and Guido Tabellini},
- title={A Positive Theory of Fiscal Deficits and Government Debt},
- journal={The Review of Economic Studies},
- volume={57},
- year={1990},
- pages={403-414},
- month={July},
- number={3}
-}
-
- at article{Alho00,
- author={J. M. Alho},
- title={Discussion},
- journal={North American Actuarial Journal},
- volume= 4,
- year= 2000,
- pages={91--93},
- number= 1
-}
-
- at article{Alho92,
- author={J. M. Alho},
- title={{Comment on ``Modeling and Forecasting U.S. Mortality'' by R. Lee and L.
- Carter}},
- journal= jasa,
- volume= 87,
- year= 1992,
- pages={673--674},
- month={September},
- number= 419
-}
-
- at article{AlSaCr76,
- author={James Alt and Bo Sarlvik and Ivor Crewe},
- title={Individual Differences Scaling and Group Attitude Structures: British Party
- Imagery in 1974},
- journal={Quality and Quantity},
- volume= 10,
- year= 1976,
- pages={297--320},
- month={October}
-}
-
- at book{AltGilMcD03,
- author={Micah Altman and Jeff Gill and Michael P. McDonald},
- title={Numerical Issues in Statistical Computing for the Social Scientist},
- publisher={John Wiley and Sons},
- year= 2003,
- address={New York}
-}
-
- at article{Altman85,
- author={Douglas G. Altman},
- title={Comparability of Randomised Groups},
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- number={1}
-}
-
- at article{Altman98,
- author={Douglas G. Altman and Jonathan J. Deeks and David L. Sackett},
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- pages= 1318,
- month={Nov. 7}
-}
-
- at article{AltMcD03,
- author={Micah Altman and Michael P. McDonald},
- title={Replication with Attention to Numerical Accuracy},
- journal={Political Analysis},
- volume={11},
- year={2003},
- pages={302-307},
- number={3}
-}
-
- at article{AltRub70,
- author={Robert P. Althauser and Donald B. Rubin},
- title={The computerized construction of a matched sample},
- journal={American Journal of Sociology},
- volume= 76,
- year= 1970,
- pages={325-346},
- month={September}
-}
-
- at article{AlvBre95,
- author={Michael R. Alvarez and John Brehm},
- title={American Ambivalence Toward Abortion Policy: A Heteroskedastic probit Method
- for Assessing Conflicting Values},
- journal={American Journal of Political Science},
- volume={39},
- year={1995},
- pages={1055-82},
- month={November}
-}
-
- at article{AlvBre97,
- author={Michael R. Alvarez and John Brehm},
- title={Are Americans Ambivalent Towards Racial Policies},
- journal={American Journal of Political Science},
- volume={41},
- year={1997},
- pages={345-374},
- month={April},
- number={2}
-}
-
- at article{AlvGarLan91,
- author={Michael R.\ Alvarez and Geoffrey Garrett and Peter Lange},
- title={Government Partisanship, Labor Organization, and Macroeconomic Performance},
- journal= apsr,
- volume= 85,
- year= 1991,
- pages={539--556}
-}
-
- at article{AmoMccZim97,
- author={A.F. Amos and D.J. McCarty and P. Zimmet},
- title={The Rising Global Burden of Diabetes and its Complications: Estimates and
- Projections to the Year 2010},
- journal={Diabetic Medicine},
- volume= 14,
- year= 1997,
- tpages={S7--S85}
-}
-
- at book{AndBasHum83,
- author={Andy B. Anderson and Alexander Basilevsky and Derek P.J. Hum},
- title={Missing Data: A Review of the Literature},
- publisher={Academic Press, Inc},
- year={1983},
- editor={Peter H. Rossi and James D. Writght and Andy B. Anderson}
-}
-
- at article{AndGib06,
- author={Krister Andersson and Clark C. Gibson},
- title={Decentralized Governance and Environmental Change: Local Institutional Moderation
- of Defroestation in Bolivia},
- journal={Journal of Policy Analysis and Management},
- volume={26},
- year={2006},
- pages={99-123},
- number={1}
-}
-
- at article{AndGreMcc05,
- author={Richard G. Anderson and William H. Greene and B.D. McCullough and H.D. Vinod},
- title={The Role of Data \& Program Code Archives in the Future of Economic Research},
- year= 2005,
- month={July},
- note={Federal Reserve Bank of St. Louis Research Division}
-}
-
- at article{Andrews91,
- author={Donald W.K. Andrews},
- title={Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation},
- journal={Econometrica},
- volume={59},
- year={1991},
- pages={817--858},
- month={May},
- number={3}
-}
-
- at article{AndZom01,
- author={A.S. Andreou and G.A. Zombanakis},
- title={A Neural Network Measurement of Relative Military Security--The Case of
- Greece and Cyprus},
- journal={Defence and Peace Economics},
- volume= 12,
- year= 2001,
- pages={303--324},
- number= 4,
- annote={have not read primary source. looks promising, given secondary source comments:
- all input variables are financial and the output variable--relative security--is
- population/demographics based. Arms race scenarios are simulated by increasing
- and decreasing financial covariates.}
-}
-
- at article{AngAngFro94,
- author={G. De Angelis and R. De Angelis and L. Frova and A. Verdecchia},
- title={MIAMOD: A Computer Package to Estimate Chronic Disease Morbidity Using Mortality
- and Survival Data},
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- volume= 44,
- year= 1994,
- pages={99--107}
-}
-
- at article{AngImb95,
- author={Joshua D. Angrist and Guido W. Imbens},
- title={Two-Stage Least Squares Estimation of Average Causal Effects in Models withVariable
- Treatment Intensity},
- journal={Journal of the American Statistical Association},
- volume={90},
- year={1995},
- pages={431-442},
- month={June},
- number={430}
-}
-
- at article{AngImbRub96,
- author={Angrist, Joshua D. and Imbens, Guido W. and Rubin, Donald B.},
- title={Identification of Causal Effects Using Instrumental Variables (with discussion)},
- journal={Journal of the American Statistical Association},
- volume={91},
- year={1996},
- pages={444--455},
- optnumber={434}
-}
-
- at article{Angress59,
- author={Werner T. Angress},
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- volume= 21,
- year= 1959,
- pages={530--549},
- number= 3
-}
-
- at unpublished{AnkBlaCol99,
- author = {Martha Anker and Robert E. Black and Christopher
- Coldham and Henry D. Kalter and Maria A. Quigley and
- David Ross and Robert W. Snow},
- title = {A Standard Verbal Autopsy Method for Investigating
- Causes of Death in Infants and Children},
- note = {World Health Organization, Department of
- communicable Disease Surveillance and Response},
- year = {1999},
- journal = {World Health Organization}
-}
-
- at book{Anker03,
- author = {Martha Anker},
- title = {Investigating Cause of Death During an Outbreak of
- Ebola Virus Haemorrhagic Fever: Draft Verbal Autopsy
- Instrument},
- publisher = {World Health Organization},
- year = 2003,
- address = {Geneva}
-}
-
- at article{Anker97,
- author = {Martha Anker},
- title = {The Effect of Misclassification Error on Reported
- Cause-Specific Mortality Fractions from Verbal
- Autopsy},
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- volume = {26},
- year = {1997},
- pages = {1090-1096}
-}
-
- at article{AppBosGra96,
- author = {A. Appels, et al},
- title = {Self-Rated Health and Mortality in a Lithuanian and
- Dutch Population},
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- volume = 42,
- year = 1996,
- pages = {{681-89}},
- number = 5
-}
-
- at techreport{Arendt03,
- author = {Jacob N. Arendt},
- title = {Social gradients in self-rated health in Denmark -
- gender differences and health risk factors in
- dynamic context},
- institution = {AKF, Institute of Local Government Studies},
- year = 2003,
- month = {May},
- address = {Nyropsgade 37, 1602 Copenhagen V, Denmark}
-}
-
- at book{Arendt73,
- author = {Arendt, Hannah},
- title = {The Origins of Totalitarianism},
- publisher = {Harcourt Brace Jovanovich},
- year = 1973,
- address = {New York}
-}
-
- at incollection{Armstrong01,
- author = {J. Scott Armstrong},
- title = {Extrapolation of Time Series and Cross-Sectional
- Data},
- booktitle = {Principles of Forecasting: A Handbook for
- Researchers and Practitioners},
- publisher = {Kluwer},
- year = 2001,
- editor = {J. Scott Armstrong},
- pages = {217--243}
-}
-
- at unpublished{Ashworth01,
- author = {Scott Ashworth},
- title = {Reputational Dynamics and Congressional Careers},
- note = {Harvard University},
- year = 2001,
- annote = {introduce the single crossing property in political
- science}
-}
-
- at article{AssPocEno00,
- author = {Susan F. Assmann and Stuart J. Pocock, Laura E. Enos
- and Linda E. Kasten},
- title = {Subgroup analysis and other (mis)uses of baseline
- data in clinical trials},
- journal = {The Lancet},
- volume = {355},
- year = {2000},
- pages = {1064-1069},
- month = {March}
-}
-
- at article{AusMam06,
- author={Peter C. Austin and Muhammad M. Mamdani},
- title={A comparison of propensity score methods: A case-study estimating the effectiveness
- of post-AMI statin use},
- journal={Statistics in Medicine},
- volume={25},
- year={2006},
- pages={2084-2106}
-}
-
- at article{AusMamStu05,
- author={Peter C. Austin and Muhammad M. Mamdani and Therese A. Stukel and Geoffrey
- M. Anderson and Jack V. Tu},
- title={The use of the propensity score for estimating treatment effects: {A}dministrative
- versus clinical data},
- journal={Statistics in Medicine},
- volume={24},
- year={2005},
- pages={1563-1578}
-}
-
- at article{AvlSchDav98,
- author={Kirsten Avlund, Kirsten Schultz-Larsen, and Michael Davidson},
- title={Tiredness in Daily Activities at Age 70 as a Predictor of Mortality During
- the Next 10 Years},
- journal={Journal of Clinical Epidemiology},
- volume= 51,
- year= 1998,
- pages={{323-33}}
-}
-
- at article{BacKin04,
- author={Bachrach, Christine A. and King, Roslind B.},
- title={{Data Sharing and Duplication: Is There a Problem?}},
- journal={Archives of Pediatric and Adolescent Medicine},
- volume= 158,
- year={2004},
- month={September},
- number= 9
-}
-
- at article{BagHopMas02,
- author={A. Bagust and P.K. Hopkinson and L. Maslove and C.J. Currie},
- title={The Projected Health Care Burden of Type 2 Diabetes in the UK from 2000
- to 2060},
- journal={Diabetic Medicine},
- volume= 19,
- year= 2002,
- pages={1--5},
- number= 4
-}
-
- at book{Balderston02,
- author={Theo Balderston},
- title={Economics and Politics in the Weimar Republic},
- publisher={Cambridge University Press},
- year= 2002,
- address={Cambridge}
-}
-
- at article{BanBan92,
- author={A.T. Bang and R.A. Bang and the SEARCH team},
- title={Diagnosis of causes of childhood deaths in developing countries by verbal
- autosy: suggested criteria},
- journal={Bulletin of the World Health Organization},
- volume={70},
- year={1992},
- pages={499-507},
- number={4}
-}
-
- at article{BaqBlaAri98,
- author={A.H. Baqui and R.E. Black and S.E. Arifeen and K. Hill and S.N. Mitra and
- A.Al Sabir},
- title={Causes of childhood deaths in Bangladesh: results of a nationwide verbal
- autopsy study},
- journal={Bulletin of the World Health Organization},
- volume={76},
- year={1998},
- pages={161},
- number={2}
-}
-
- at article{BarFraHil03,
- author={John Barnard and Constantine E. Frangakis and Jennifer L. Hill and Donald
- B. Rubin},
- title={{Principal Stratification Approach to Broken Randomized Experiments: A Case
- Study of School Choice Vouchers in New York City.}},
- journal={Journal of the American Statistical Association},
- volume={98},
- year={2003},
- pages={299-324},
- number={462}
-}
-
- at book{Barkai90,
- author={Barkai, Avram},
- title={Nazi Economics: Ideology, Theory, and Policy},
- address={Oxford},
- publisher={Berg Press},
- year={1990}
-}
-
- at article{BarPonCor00,
- author={Ivana C. H. C. Barr{\^e}to and L{\'i}gia Kerr Pontes and e Luciano Corr{\^e}a},
- title={Vigil{\^a}ncia de {\'o}bitos infantis em sistemas locais de sa{\'u}de: avalia{\c{c}}{\~a}o da
- aut{\'o}psia verbal e das informa{\c{c}}{\~o}es de agentes de sa{\'u}de},
- journal={Rev Panam Salud Publica / Pan Am Journal of Public Health},
- volume={7},
- year={2000},
- pages={303-312},
- number={5}
-}
-
- at article{Bartels96,
- author={Bartels, Larry M.},
- title={Uninformed Votes: Information Effects in Presidential Elections},
- journal={American Journal of Political Science},
- volume= 40,
- year= 1996,
- pages={194--230}
-}
-
- at unpublished{Bartels98,
- author={Larry Bartels},
- title={Panel Attrition and Panel Conditioning in American National Election Sudies},
- note={Paper prepared for the 1998 meetings of the Society for Political Methodology,
- San Deigo},
- year={1998}
-}
-
- at article{BasEst01,
- author={S.A. Bashir and J. Esteve},
- title={Projecting Cancer Incidence and Mortality Using Bayesian Age-Period-Cohort
- Models},
- journal={Journal of Epidemiology and Biostatistics},
- volume= 6,
- year= 2001,
- pages={287--296},
- number= 3
-}
-
- at unpublished{BatFerHab06,
- author={Robert Bates and Karen Feree and James Habyarimana and Macartan Humphreys
- and Smita Singh},
- title={The Africa Research Program},
- note={{http://africa.gov.harvard.edu}},
- year= 2006
-}
-
- at article{Bath03,
- author={Peter A. Bath, PhD},
- title={Differences Between Older Men and Women in the Self-Rated Health-Mortality
- Relationship},
- journal={The Gerontologist},
- volume= 43,
- year= 2003,
- pages={{387-95}}
-}
-
- at article{Baum88,
- author={Lawrence Baum},
- title={Measuring Policy Change in the U.S. Supreme Court},
- journal= apsr,
- volume= 82,
- year= 1988,
- pages={905--912},
- month={September},
- number= 3
-}
-
- at article{BeaMei89,
- author={Michael L. Beach and Paul Meier},
- title={Choosing Covariates in the Analysis of Clinical Trials},
- journal={Controlled Clinical Trials},
- volume={10},
- year={1989},
- pages={161S-175S}
-}
-
- at incollection{Bearce00,
- author={David Bearce},
- title={Economic Sanctions and Neural Networks: Forecasting Effectiveness and Reconsidering
- Cooperation},
- booktitle={Political Complexity: Non Linear Models of Politics},
- publisher={University of Michigan Press},
- year= 2000,
- address={Ann Arbor, MI},
- editor={Diana Richards},
- pages={269--295},
- annote={asks whether real-world forecasting needs make NN preferable to traditional
- (and linear) analysis. Looks at effectiveness of sanctions, using about
- 100 quantitative cases first examined in 1980s. NNs are shown to forecast
- twice as well as traditional methods.}
-}
-
- at book{BecChaWil88,
- author={Richard A. Becker and John M. Chambers and Allan R. Wilks},
- title={The New S. language},
- publisher={Wadsworth},
- year={1988},
- address={New York}
-}
-
- at article{BecIch02,
- author={Sascha O. Becker and Andrea Ichino},
- title={Estimation of average treatment effects based on propensity scores},
- journal={The Stata Journal},
- volume= 2,
- year= 2002,
- pages={358-377},
- number= 4
-}
-
- at article{BecIch02,
- author={Sascha O. Becker and Andrea Ichino},
- title={Stata programs for ATT estimation based on propensity score matching},
- journal={The Stata Journal},
- volume= 2,
- year= 2002,
- pages={358--377},
- number= 4
-}
-
- at article{BecJac98,
- author={Nathaniel Beck and Simon Jackman},
- title={Beyond Linearity by Default: Generalized Additive Model},
- journal= ajps,
- volume= 42,
- year= 1998,
- pages={596--627},
- month={April},
- number= 2
-}
-
- at article{BecKat95,
- author={Nathaniel Beck and Jonathan Katz},
- title={``What to Do (and Not to Do) with Time-Series-Cross-Section Data''},
- journal= apsr,
- volume= 89,
- year= 1995,
- pages={634--647}
-}
-
- at article{BecKat96,
- author={Nathaniel Beck and Jonathan Katz},
- title={Nuisance vs. Substance: Specifying and Estimating Time-Series-Cross-Section
- Model},
- journal= pa,
- volume={VI},
- year= 1996,
- pages={1--36}
-}
-
- at article{BecKatTuc98,
- author={Nathaniel Beck and Jonathan Katz and Richard Tucker},
- title={Taking Time Seriously: Time-Series-Cross-Section Analysis with a Binary
- Dependent Variable},
- journal= apsr,
- volume= 42,
- year= 1998,
- pages={1260-1288}
-}
-
- at article{BedChrJoh96,
- author={Edward J. Bedrick and Ronald Christensen and Wesley Johnson},
- title={A New Perspective on Priors for Generalized Linear models},
- journal={Journal of the American Statistical Association},
- volume={91},
- year={1996},
- pages={1450-1460},
- number={436}
-}
-
- at techreport{BehTod99,
- author={Jere R. Behrman and Petra E. Todd},
- title={Randomness in the Experimental Samples of Progresa (Education, Health, and
- Nutrition Program)},
- institution={International Food Policy Research Institute},
- year={1999},
- month={March},
- type={Research Report},
- address={2033 K Street, NW Washington, DC 20006}
-}
-
- at article{Bell97,
- author={W.R. Bell},
- title={{Comparing and Assessing Time Series Methods for Forecasting Age-Specific
- Fertility and Mortality Rates}},
- journal={Journal of Official Statistics},
- volume= 13,
- year= 1997,
- pages={279--303},
- number= 3
-}
-
- at article{Bello93,
- author={Abdul Lateef Bello},
- title={Choosing Among Imputation Techniques for Incomplete Multivariate Data: A
- Simulation Study},
- journal={Communications in Statistics A: Theory and Methods},
- volume={22},
- year={1993},
- pages={853-877},
- number={3}
-}
-
- at article{BelMon91,
- author={W.R. Bell and B.C. Monsell},
- title={Using Principal Components in time Series modeling and Forecasting of Age-Specific
- Mortality Rates},
- journal={Proceedings of the American Statistical Association, Social Statistics Section},
- year= 1991,
- pages={154--159}
-}
-
- at article{Beltrami1873,
- author={E. Beltrami},
- title={Sulle funzioni bilineari},
- journal={Giornale di Matematiche ad Uso degli Studenti Delle Universit{\'a}},
- volume= 11,
- year= 1873,
- pages={98--106},
- note={{An English translation by D. Boley is available as University of Minnesota,
- Department of Computer Science, Technical Report 90-37, 1990}}
-}
-
- at article{BenBluLus03,
- author={Yael Benyamini, et al.},
- title={Gender differences in the self-rated health-mortality association: Is it
- poor self-rated health that predicts mortality or excellent self-rated
- health that predicts survival?},
- journal={The Gerontologist},
- volume={43},
- year={2003},
- pages={{396-405}},
- number={3}
-}
-
- at incollection{Bendix53,
- author={Bendix, Reinhard},
- title={Social Stratification and Political Power},
- booktitle={Class Status and Power},
- publisher={The Free Press},
- year= 1953,
- address={Glencoe, IL},
- editor={Bendix, Reinhard and Lipset, Seymour Martin}
-}
-
- at article{BenHumEbe04,
- author={Maureen Reindl Benjamins},
- title={Self-Reported Health and Adult Mortality Risk: An Analysis of Cause Specific
- Mortality},
- journal={Social Science and Medicine (Forthcoming 2004)}
-}
-
- at article{benichou95,
- author={J. Benichou and M. Gail},
- title={Methods of Inference for Estimates of Absolute Risk Derived From Population-Based
- Case-Control Studies},
- journal={Biometrics},
- volume= 51,
- year= 1995,
- pages={182-194}
-}
-
- at article{BenIdl99,
- author={Yael Benyamini, and Ellen Idler},
- title={Community Studies Reporting Association Between Self-Rated Health and Mortality},
- journal={Research on Aging},
- volume= 21,
- year= 1999,
- pages={{392-401}},
- number= 3
-}
-
- at article{BenIdlLev00,
- author={Yael Benyamini, Ellen Idler, Howard Leventhal, and Elaine A. Leventhal},
- title={Positive-Affect and Function as Influences on Self-Assessments of Health:
- Expanding ou View Beyond Illness and Disability},
- journal={Journal of Gerontology: Psychological Sciences},
- volume={{55B}},
- year= 2000,
- pages={{P107-116}}
-}
-
- at article{BenLav03,
- author={Kenneth Benoit and Michael Laver},
- title={Estimating Irish party policy positions using computer wordscoring: the
- 2002 election - a research note},
- journal={Irish Political Studies},
- volume={18},
- year={2003},
- pages={97--107},
- number={1}
-}
-
- at article{BenLevLev00,
- author={Yael Benyamini, et al},
- title={Gender Differences in Processing Information for Making Self-Assessments
- of Health },
- journal={American Psychosomatic Society},
- volume= 62,
- year= 2000,
- pages={{354-64}},
- number= 2
-}
-
- at article{BenLevLev99,
- author={Yael Benyamini, Elaine A. Leventhal, and Howard Leventhal},
- title={Self-Assessments of Health. What Do People Know that Predicts their Mortality?},
- journal={Reasearch on Aging},
- volume= 21,
- year= 1999,
- pages={{477-500}},
- month={{May}},
- number= 3
-}
-
- at article{BenLip59,
- author={Bendix, Reinhard and Lipset, Seymour Martin},
- title={On the Social Structure of Western Societies: Some Reflections on Comparative
- Analysis},
- journal={Berkeley Journal of Sociology},
- volume= 5,
- year= 1959,
- pages={1-15}
-}
-
- at article{BenSin99,
- author={S.K. Benara and Padam Singh},
- title={Validity of Causes of Infant Death by Verbal Autopsy},
- journal={Indian Journal of Pediatrics},
- volume={66},
- year={1999},
- pages={647-650}
-}
-
- at article{BenSin99,
- author={S.K. Benara and Padam Singh},
- title={Validity of Causes of Infant Death by Verbal Autopsy},
- journal={Indian Journal of Pediatrics},
- volume={66},
- year={1999},
- pages={647-650}
-}
-
- at article{BerdeG47,
- author={Berelson, B. and de Grazia, S.},
- title={{Detecting Collaboration in Propaganda}},
- journal={Public Opinion Quarterly},
- volume={11},
- year={1947},
- pages={244--253},
- number={2}
-}
-
- at proceedings{BerDegLin88,
- editor={J. M. Bernardo and M.H. Degroot and D.V. Lindley and A.F.M. Smith},
- title={Bayesian Statistics 3},
- publisher={Clarendon Press, Oxford},
- year={1987},
- month={June 1-5},
- organization={Proceedings of the Third Valencia International Meeting}
-}
-
- at article{Berenson04,
- author={Robert Berenson},
- title={The Medicare Chronic Care Improvement Program},
- journal={The Urban Institute},
- year={2004},
- month={May},
- note={{http://www.urban.org/url.cfm?ID=900714}}
-}
-
- at article{Berger04,
- author={Vance W. Berger},
- title={Selection Bias and Baseline Imbalances in Randomized Trials},
- journal={Drug Information Journal},
- volume={38},
- year={2004},
- pages={1-2}
-}
-
- at article{Berger05a,
- author={Vance W. Berger},
- title={Quantifying the Magnitude of Baseline Covariate Imbalances Resulting fronmSelection
- Bias in Randomized Clinical Trials},
- journal={Biometrical Journal},
- volume={47},
- year={2005},
- pages={119-127},
- number={2}
-}
-
- at book{Berger05b,
- author={Vance W. Berger},
- title={Selection Bias and covariate Imbalances in Randomized Clinical Trials},
- publisher={John Wiley \& Sons, Ltd.},
- year={2005},
- editor={Stephen Senn and Vic Barnett},
- series={Statistics in Practice}
-}
-
- at article{Berger94,
- author={James Berger},
- title={An Overview of Robust Bayesian Analysis (With Discussion)},
- journal={Test},
- volume= 3,
- year= 1994,
- pages={5-124}
-}
-
- at article{BerHenSav77,
- author={E. Berndt and D. Hendry and N.E. Savin},
- title={Conflict Among Criteria for Testing Hypotheses in the Multivariate Linear
- Regression Model},
- journal={Econometrica},
- volume={45},
- year={1977},
- pages={1263-1277}
-}
-
- at article{BerKinKon97,
- author={Shulamit L. Bernard, Jean E. Kincade, Thomas R. Conrad, et al},
- title={Predicting Mortality from Community Surveys of Older Adults: The Importance
- of Self-Rated Functional Ability},
- journal={Journal of Gerontology: Social Sciences},
- volume={{52B}},
- year= 1997,
- pages={{S155-63}}
-}
-
- at misc{BerKos03,
- author={Erik Bergstralh and Jon Kosanke},
- title={dist, gmatch, and vmatch: SAS Macros},
- year= 2003,
- howpublished={Mayo Clinic, Division of Biostatistics},
- note={{http://mayoresearch.mayo.edu/mayo/research/biostat/sasmacros.cfm}}
-}
-
- at book{BerKreOve98,
- author={Mark de Berg and Marc van Krevald and Mark Overmars and Otfried Schwarzkopf},
- title={Computational Geometry: Algorithms and Applications},
- publisher={Springer},
- year= 1998,
- address={New York},
- edition={2nd, revised edition}
-}
-
-
- at book{ImbRub10,
- author={Guido Imbens and Donald Rubin},
- title={Causal Inference},
- year= {2010},
- note={Unpublished manuscript}
-}
-
-
- at article{Bernstein32,
- author={F. Bernstein},
- title={{\"U}ber eine Methode, die soziologische und bev{\"o}lkerungsstatistische Gliederung
- von Abstimmungen bei geheimen Wahlverfahren zu ermittlen},
- journal={Allgemeines Statistisches Archiv},
- volume= 22,
- year= 1932,
- pages={253--256}
-}
-
- at article{Besag74,
- author={Julian Besag},
- title={Spatial Interaction and the Statistical Analysis of Lattice Systems (With
- Discussion)},
- journal= jrssb,
- volume= 36,
- year= 1974,
- pages={192-236}
-}
-
- at article{Besag75,
- author={Julian Besag},
- title={Statistical Analysis of Non-Lattice Data},
- journal={The Statistician},
- volume= 24,
- year= 1975,
- pages={179--195},
- number= 3
-}
-
- at article{Besag83,
- author={Julian E. Besag},
- title={Discussion of paper by {P}. {S}witzer},
- journal={Bull. Intern. Statist. Inst.},
- volume= 50,
- year= 1983,
- pages={422-425},
- number={Bk. 3}
-}
-
- at article{Besag86,
- author={Julian Besag},
- title={On the Statistical Analysis of Dirty Pictures},
- journal={Journal of the Royal Statistical Society B},
- volume={48},
- year={1986},
- pages={259--302},
- number={3}
-}
-
- at article{Besancon05,
- author={Marie L. Besancon},
- title={Relative Resources: Inequality in Ethnic Wars, Revolutions, and Genocides},
- abstract={Political scientists and economists have exhaustively examined the nexus
- between economic inequality and political conflict (EI-PC nexus) in aggregated
- civil wars. This article revisits the nexus and its related theories, empirically
- and parsimoniously testing the effects of inequality on disaggregated intrastate
- conflicts. The results buttress the notion that traditionally deprived
- identity groups are more likely to engage in conflict under more economically
- equal conditions, while class or revolutionary wars fall under the conditions
- of greater economic inequality and war. Of the three types of conflicts
- tested - ethnic conflicts, revolutions, and genocides - economic inequality
- seems to have the most ambiguous bearing on genocides. Support follows
- for recent findings that political and social equalities are of greater
- importance in mitigating ethnic violence and that greed factors might exacerbate
- violence in all civil conflicts, including genocides. The theoretical argument
- proposes that the context within which intrastate violence takes place
- affects the requisite level of relative resources needed for the escalation
- of violence between groups. The results have policy implications for ethnically
- divided states that are in the process of equalizing their income differential,
- but neglect the substantial inclusion of all groups within the political
- process and the distribution of public goods. The social contracts between
- the governors and the governed then require careful crafting for a peaceful
- coexistence of diverse identity groups.},
- journal={The Journal of Peace Research},
- volume={42},
- year={2005},
- pages={393-415},
- month={July},
- number={4}
-}
-
- at article{BesGreHigMen95,
- author={Julian Besag and Peter Green and David Higdon and Kerrie Mengersen},
- title={Bayesian Computation and Stochastic Systems (With Discussion)},
- journal={Statistical Science},
- volume= 10,
- year= 1995,
- pages={3-66},
- number= 1
-}
-
- at article{BesHig99,
- author={Julian Besag and David M. Higdon},
- title={Bayesian Analysis of Agricultural Field Experiments (With Discussion)},
- journal= jrssb,
- volume= 61,
- year= 1999,
- pages={691-746},
- number={4}
-}
-
- at article{BesKoo95,
- author={Julian Besag and Charles Kooperberg},
- title={On Conditional and Intrinsic Autoregressions},
- journal={Biometrika},
- volume={82},
- year= 1995,
- pages={733-746},
- number={4}
-}
-
- at article{BesYorMol91,
- author={Julian Besag and Jeremy York and Annie Molli{\'e}},
- title={Bayesian Image Restoration with Two Applications in Spatial Statistics (With
- Discussion)},
- journal={Annals of the Institute of Statistical Mathematics},
- volume= 43,
- year= 1991,
- pages={1-59},
- number= 1
-}
-
- at article{Bicego97,
- author={G. Bicego},
- title={Estimating adult mortality rates in the context of the AIDS epidemic in
- sub-Saharan Africa: analysis of DHS sibling histories},
- journal={Health Transition Review},
- volume= 7,
- year= 1997,
- pages={7--22},
- number={S2}
-}
-
- at book{Biggs93,
- author={N.L. Biggs},
- title={Algebraic Graph Theory},
- publisher={Cambridge University Press},
- year= 1993,
- address={Cambridge, UK},
- edition={2nd}
-}
-
- at article{Billordo05a,
- author={Libia Billordo},
- title={Publishing in French Political Science Journals},
- journal={French Politics},
- volume={3},
- year={2005},
- pages={178-186},
- number={2}
-}
-
- at article{Billordo05b,
- author={Libia Billordo},
- title={Methods Training in French Political Science},
- journal={French Politics},
- volume={3},
- year={2005},
- pages={352-0357},
- number={3}
-}
-
- at article{BinBreEar05,
- author={J.B. Bingenheimer and R.T. Brennan and F.J. Earls},
- title={Firearm violence exposure and serious violent behavior},
- journal={Science},
- volume={308},
- year={2005},
- pages={1323-1326},
- month={May}
-}
-
- at book{BisFieHol75,
- author={Y.M. M. Bishop and S.E. Fienberg and P.W. Holland},
- title={Multivariate Analysis: Theory and Practice},
- publisher={MIT Press},
- year= 1975,
- address={Cambridge, MA}
-}
-
- at book{Bishop95,
- author={Christopher M. Bishop},
- title={Neural Networks for Pattern Recognition},
- publisher={Oxford University Press},
- year= 1995,
- address={Oxford}
-}
-
- at article{BisSteWil06,
- author={Benjamin Bishin and Daniel Stevens and Christian Wilson},
- title={{Character Counts: Honesty and Fairness in Election 2000}},
- journal={Public Opinion Quarterly},
- volume={70},
- year={2006},
- pages={235-248},
- number={2}
-}
-
- at article{BjoKri99,
- author={Jakob Bue Bjorner and Tage Sondergaard Kristensen},
- title={Multi-item Scales for Measuring Global Self Rated Health},
- journal={Research on Aging},
- volume= 21,
- year= 1999,
- pages={{417-39}},
- number= 3
-}
-
- at article{BlaGeo91,
- author={R.C. Blattberg and E.I. George},
- title={Shrinkage Estimation of Price and Promotional Elasticities: Seemingly Unrelated
- Equations},
- journal= jasa,
- volume= 86,
- year= 1991,
- pages={304--315},
- month={Jun},
- number= 414
-}
-
- at article{BlaRas04,
- author={Grant Blank and Karsten B. Rasmussen},
- title={The Data Documentation Initiative: The Value and Significance of a Worldwide
- Standard.},
- journal={Social Science Computer Review},
- volume={22},
- year={2004},
- pages={306-318},
- number={3}
-}
-
- at article{BlaSmi04,
- author={Dan A. Black and Jeffrey A. Smith},
- title={How robust is the evidence on the effects of college quality? Evidence from
- matching},
- journal={Journal of Econometrics},
- volume={121},
- year={2004},
- pages={99-124},
- number={1}
-}
-
- at article{BloHilRic03,
- author={Howard S. Bloom and Carolyn J. Hill and James A. Riccio},
- title={Linking Program Implementation and Effectiveness: Lessons from a Pooled
- Sample of Welfare-to-Work Experiments},
- journal={Journal of Policy Analysis and Management},
- volume={22},
- year={2003},
- pages={551-575},
- number={4}
-}
-
- at book{Bloom05,
- title={Learning More from Social Experiments},
- publisher={Russell Sage Foundation},
- year={2005},
- editor={Howard S. Bloom},
- address={New York}
-}
-
- at article{BloRicBla07,
- author={Howard S. Bloom and Lashawn Richburg-Hayes and Alison Black},
- title={Using Covariates to Improve Precision for Studies that Randomize Schools
- to Evaluate Educational Interventions},
- journal={Educational Evaluation and Policy Analysis},
- year={2007}
-}
-
- at book{BLS03,
- author={{Board on Life Sciences}},
- title={Sharing Publication-Related Data and Materials: Responsibilities of Authorship
- in the Life Sciences},
- publisher={National Academies Press},
- year= 2003,
- address={Washington, D.C.}
-}
-
- at article{Blumer48,
- author = {Herbert Blumer},
- title = {Public Opinion and Public Opinion Polling},
- journal = {American Sociological Review},
- volume = {13},
- year = {1948},
- pages = {542-549},
- month = {October},
- number = {5}
-}
-
- at incollection{Bohm84,
- author={Peter Bohm},
- title={Are thee Practicable Demand-Revealing Mechanisms?},
- booktitle={Public Finance and the Quest for Efficiency},
- publisher={Wayne State University Press},
- year={1984},
- address={Detroit},
- editor={H. Hanusch},
- pages={127-139}
-}
-
- at article{BonBarMee94,
- author={Luc Monneux and Jan J. Barendregt and Karin Meeter and Gouke J. Bonsel and
- Paul J. van der Maas},
- title={Estimating Clinical Morbidity Due to Ischemic Heart Disease and Congestive
- Heart Failure: The Future Rise of Heart Failure},
- journal={American Journal of Public Health},
- volume= 84,
- year= 1994,
- pages={20-28}
-}
-
- at unpublished{BonBonJen01,
- author={Doug Bond and Joe Bond and J. Craig Jenkins and Churl Oh and Charles Lewis
- Taylor},
- title={Integrated Data for Events Analysis (IDEA): An Event Form Typology for Automated
- Events Data Development},
- note={manuscript, Harvard University},
- year= 2001
-}
-
- at article{Bongaarts89,
- author={John Bongaarts},
- title={A Model of the Spread of HIV Infection and the Demographic Impact of AIDS},
- journal={Statistics in Medicine},
- volume= 8,
- year= 1989,
- pages={103--120}
-}
-
- at techreport{BooMaiSmi02,
- author={Heather Booth and John Maindonald and Len Smith},
- title={{Age-Time Interactions in Mortality Projection: Applying Lee-Carter to Australia}},
- institution={The Australian National University},
- year= 2002,
- month={August},
- type={Working Papers in Demography}
-}
-
- at article{BooMaiSmi02b,
- author={Heather Booth and John Maindonald and Len Smith},
- title={Applying Lee-Carter Under Conditions of Variable Mortality Decline},
- journal={Population Studies},
- volume= 56,
- year= 2002,
- pages={325--336},
- number= 3
-}
-
- at unpublished{BorBorRal01,
- author={Roman Borisyuk and Galina Borisyuk and Colin Rallings and Michael Thrasher},
- title={Forecasting the 2001 General Election Result: A Neural Network Approach},
- note={{http://www.psa.ac.uk/spgrp/epop/forecasting\_genelect2001.htm}},
- year={2001},
- annote={authors try to forecast election results; they generate fitted values by
- 'predicting' the winners of past elections. they do break up their data
- sets into training and test in the spirit of cross-validation; they also
- compare their results to logit.}
-}
-
- at incollection{Borchardt91,
- author = {Knut Borchardt},
- title = {Economic Causes for the Collapse of the Weimar
- Republic},
- booktitle = {Perspectives on Modern German Economic History and
- Policy},
- publisher = {Cambridge University Press},
- year = 1991,
- address = {New York},
- editor = {Knut Borchardt},
- pages = {161--184}
-}
-
- at article{borgan95,
- author={{\O }rnulf Borgan and B. Langgholz and L. Goldstein},
- title={Methods for the Analysis of Sampled Cohort Data in the Cox Proportional
- Hazard Model},
- journal={The Annals of Statistics},
- volume= 23,
- year= 1995,
- number={1749-1778}
-}
-
- at article{BorMayTur04,
- author={Robert Boruch and Henry May and Herbert Turner and Julia Lavenberg and Anthony
- Petrosino and Dorothy de Moya and Jeremy Grimshaw and Ellen Foley },
- title={Estimating the Effects of Interventions That are Deployed in Many Places:
- Place-Randomized Trials},
- journal={American Behavioral Scientist},
- volume={47},
- year={2004},
- pages={608-633},
- number={5}
-}
-
- at book{Boruch97,
- author={Robert F. Boruch},
- title={Randomized Experiments for Planning and Evaluation},
- publisher={Sage Publications},
- year={1997},
- address={Thousand Oaks}
-}
-
- at article{BouChaWel01,
- author={Andrew Boulle and Daniel Chandramohan and Peter Weller},
- title={A Case Study of Using Artificial Neural Networks for Classifying Cause of
- Death from Verbal Autopsy},
- journal={International Journal of Epidemiology},
- volume={30},
- year={2001},
- pages={515-520}
-}
-
- at unpublished{BowHan05,
- author={Jake Bowers and Ben Hansen},
- title={Attributing Effects to A Cluster Randomized Get-Out-The-Vote Campaign: An
- Application of Randomization Inference Using Full Matching},
- note={Departments of Political Science and Statistics: University of Michigan},
- year={2005},
- month={July}
-}
-
- at book{BoxHunHun78,
- author={George E.P. Box and William G. Hunger and J. Stuart Hunter},
- title={Statistics for Experimenters},
- publisher={Wiley-Interscience},
- year={1978},
- address={New York}
-}
-
- at article{BoyHonNar01,
- author={James P. Boyle and Amanda A. Honeycutt and K.M. Venkat Narayan and Thomas
- J. Hoerger and Linda S. Geiss and Hong Chen and Theodore J. Thompson},
- title={Projection of Diabetes Burden Through 2050},
- journal={Diabetes Care},
- volume= 24,
- year= 2001,
- pages={1936--1940},
- number= 11
-}
-
- at article{BozBel87,
- author={J.E. Bozik and W.R. Bell},
- title={Forecasting Age Specific Fertility Using Principal Components},
- journal={Proceedings of the Americal Statistical Association, Social Statistics Section},
- year= 1987,
- pages={396--401}
-}
-
- at article{bracken98,
- author={Michael B. and John C. Bracken},
- title={Avoidable Systematic Error in Estimating Treatment Effects Must not be Tolerated},
- journal={British Medical Journal},
- volume= 317,
- year= 1998,
- pages={11-56},
- month={October 24}
-}
-
- at article{Brady85,
- author={Henry E. Brady},
- title={The Perils of Survey Research: Inter-Personally Incomparable Responses},
- journal={Political Methodology},
- volume= 11,
- year= 1985,
- pages={269--290},
- month={June},
- number={3--4}
-}
-
- at article{Brady89,
- author={Henry E. Brady},
- title={Factor and Ideal Point Analysis for Interpersonally Incomparable Data},
- journal={Psychometrika},
- volume= 54,
- year= 1989,
- pages={181--202},
- month={June},
- number= 2
-}
-
- at inproceedings{BraHil73,
- author={William Brass and Kenneth Hill},
- title={Estimating Adult Mortality in Africa from Orphanhood},
- booktitle={Proceedings of the International Population Conference Liege},
- year= 1973,
- organization={International Union for the Scientific Study of Population}
-}
-
- at article{BraTuc01,
- author={Ted Brader and Joshua Tucker},
- title={The Emergence of Mass Partisanship in Russia, 1993-96},
- journal={American Journal of Political Science},
- volume={45},
- year={2001},
- pages={69-83}
-}
-
- at book{BreDay80,
- author={Norman E. Breslow and N.E. Day },
- title={Methods in Cancer Research},
- publisher={Lyon},
- year= 1980
-}
-
- at book{BreFriOls84,
- author={Leo Breiman and Jerome H. Friedman and Richard A. Olshen and Charles J.
- Stone},
- title={Classification and Regression Trees},
- publisher={Chapman \& Hall},
- year={1984},
- address={New York, New York}
-}
-
- at book{Brehm93,
- author={John Brehm},
- title={The Phantom Respondents: Opinion Surveys and Political Respresentation},
- publisher={University of Michigan Press},
- year={1993},
- address={Ann Arbor}
-}
-
- at article{Breiman01,
- author={Leo Breiman},
- title={Statistical Modeling: The Two Cultures},
- journal={Statistical Science},
- volume={16},
- year={2001},
- pages={199-215},
- month={August},
- number={3}
-}
-
- at article{Breslow96,
- author={Norman E. Breslow},
- title={Statistics in Epidemiology: The Case-Control Study},
- journal= jasa,
- volume= 91,
- year= 1996,
- pages={14--28}
-}
-
- at unpublished{Breyer04,
- author={L.A. Breyer},
- title={The Dbacl Text Classifier},
- note={laird at lbreyer.com},
- year={04},
- month={June}
-}
-
- at unpublished{Breyer04,
- author={L.A. Breyer},
- title={The Dbacl Text Classifier},
- note={laird at lbreyer.com},
- year={04},
- month={June}
-}
-
- at article{BreZie92,
- author={Hermann Brenner and Hartwig Ziegler},
- title={Monitoring and Projecting Cancer Incidence in Saarland, Germany, Based on
- Age-Cohort Analyses},
- journal={Journal of Epidemiology and Community Health},
- volume= 46,
- year= 1992,
- pages={15--20}
-}
-
- at book{BroDav91,
- author={Peter J. Brockwell and Richard A. Davis},
- title={Time Series: Theory and Methods},
- publisher={Springer-Verlag},
- year={1991},
- edition={2nd}
-}
-
- at article{BroDenVer02,
- author={N. Brouhns and M. Denuit and J. Vermunt},
- title={A Poisson Log-bilinear Regression Approach to the Construction of Projected
- Lifetables},
- journal={Insurance: Mathematics and Economics},
- volume= 31,
- year= 2002,
- pages={373--393}
-}
-
- at article{BroGra00,
- author={Ron Brookmeyer and Sarah Gray},
- title={Methods for Projecting the Incidence and Prevalence of Chronic Diseases
- in Ageing Populations: Application to Alzheimer's Disease},
- journal={Statistics in Medicine},
- volume= 19,
- year= 2000,
- pages={1481--1493}
-}
-
- at article{BroHew00,
- author={M. Brockerhoff and P. Hewett},
- title={Inequality of child mortality among ethnic groups in sub-Saharan Africa},
- journal= bull,
- year={2000},
- optnumber={1},
- optvolume={78},
- optpages={30--41}
-}
-
- at article{Bronnum-Hansen02,
- author={Henrik Bronnum-Hansen},
- title={Predicting the Effect of Prevention of Ischaemic Heart Disease},
- journal={Scandinavian Journal of Public Health},
- volume= 30,
- year= 2002,
- pages={5--11}
-}
-
- at article{Bronnum-Hansen99,
- author={Henrik Bronnum-Hansen},
- title={How Good is the Prevent Model for Estimating the Health Benefits of Prevention?},
- journal={Journal of Epidemiology and Community Health},
- volume= 53,
- year= 1999,
- pages={300--305}
-}
-
- at article{BroSchRot06,
- author={M. Alan Brookhart and Sebastian Schneeweiss and Kenneth J. Rothman and Robert
- J. Glynn and Jerry Avorn and Til Sturmer},
- title={Variable Selection for Propensity Score Models},
- journal={American Journal of Epidemiology},
- volume={163},
- year={2006},
- pages={1149-1156},
- month={April}
-}
-
- at book{Brown58,
- author={Ralph Brown},
- title={Loyalty and Security},
- publisher={Yale University Press},
- year= 1958,
- address={New Haven, CT}
-}
-
- at article{Brown82,
- author={Brown, Courtney},
- title={The Nazi Vote: A National Ecological Study},
- journal={American Political Science Review},
- volume= 76,
- year= 1982,
- pages={285-302},
- number= 2
-}
-
- at article{BruFal94,
- author={Brustein, William and Falter, J{\"u}rgen W.},
- title={The Sociology of Nazism: An Interest-Based Account},
- journal={Rationality and Society},
- volume= 6,
- year= 1994,
- pages={369-399},
- number= 3
-}
-
- at book{Brustein96,
- author={William Brustein},
- title={The Logic of Evil: Social Origins of the Nazi Party, 1925-1933},
- publisher={Yale University Press},
- year= 1996
-}
-
- at article{BruUrd05,
- author={Helge Brunborg and Henrik Urdal},
- title={The Demography of Conflict and Violence: An Introduction},
- abstract={The demography of armed conflict is an emerging field among demographers
- and peace researchers alike. The articles in this special issue treat demography
- as both a cause and a consequence of armed conflict, and they carry important
- policy implications. A study of German-allied countries during World War
- II addresses the role of refugees and territorial loss in paving the way
- for genocide. Other articles focusing on the demographic causes of conflict
- discuss highly contentious issues of whether economic and social inequality,
- high population pressure on natural resources, and youth bulges and limited
- migration opportunities can lead to different forms of armed conflict and
- state failure. The articles on demographic responses to armed conflict
- analyze the destructiveness of pre-industrial warfare, differences in short-
- and long-term mortality trends after armed conflict, and migratory responses
- in war. Another set of articles on demographic responses to war is published
- simultaneously in the European Journal of Population.},
- journal={The Journal of Peace Research},
- volume={42},
- year={2005},
- pages={371-374},
- month={July},
- number={4}
-}
-
- at book{BSER02,
- author={{Board on Earth Sciences and Resources}},
- title={Geoscience Data and Collections: National Resources in Peril},
- publisher={National Academies Press},
- year= 2002,
- address={Washington, D.C.}
-}
-
- at article{Buchheim03,
- author={Christoph Buchheim},
- title={Die Erholung von der Weltwirtschaftskrise 1932/33 in Deutschland},
- journal={Jahrbuch fuer Wirtschaftsgeschicht},
- year={2003},
- pages={13-26},
- number={1}
-}
-
- at article{BurFred01,
- author={B Burstrom and P Fredlund},
- title={Self-rated health: Is it as good a predictor of subsequent mortality among
- adults in lower as well as in higher social classes?},
- journal={Journal of Epidemiology and Community Health},
- volume= 55,
- year= 2001,
- pages={{836-40}}
-}
-
- at article{Burgoon06,
- author={Brian Burgoon},
- title={On Welfare and Terror},
- journal={Journal of Conflict Resolution},
- volume={50},
- year={2006},
- pages={176-203},
- month={April},
- number={2}
-}
-
- at article{Burnham72,
- author={Walter Dean Burnham},
- title={Political Immunisation and Political Confessionalism: The United States
- and Weimar Germany},
- journal={Journal of Interdisciplinary History},
- volume= 3,
- year= 1972,
- pages={1--30}
-}
-
- at article{Burtless95,
- author={Gary Burtless},
- title={The Case for Randomized Field Trials in Economic and Policy Research},
- journal={The Journal of Economic Perspectives},
- volume={9},
- year={1995},
- pages={63-84},
- number={2}
-}
-
- at article{ButBurMit87,
- author={J.S. Butler, et al.},
- title={Measurement Error in Self-Reported Health Variables},
- journal={The Review of Economics and Statistics},
- volume= 69,
- year= 1987,
- pages={{644-50}}
-}
-
- at techreport{ButCar01,
- author={C.T.\ Butts and K.M.\ Carley},
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- note={Dept. of Computer Science Bar-Ilan University, Ramat-Gan Israel koppel,schlerj at cs.biu.ac.il},
- year={05}
-}
-
- at article{KorJorLet99,
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-}
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- author={Kornhauser, W.},
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-}
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- at article{KorWilGou03,
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- Dye and Robert W. Snow},
- title={Measurement of trends in childhood malaria mortality in Africa: an assessment
- of progress toward targets based on verbal autopsy},
- journal={The Lancet Infectious Diseases},
- volume={3},
- year={2003},
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-}
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- author={Koshar, R.},
- title={Social Life, Local Politics, and Nazism},
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- and Ernst Fehr},
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- volume={435},
- year={2005},
- pages={673-676},
- month={June}
-}
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- author={Neal M. Krause, PhD, and Gina M. Jay, PhD},
- title={What do Global Self-Rated Health Items Measure?},
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- pages={{930-42}}
-}
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- author={M.S. Kramer and S.H. Shapiro},
- title={{Scientific challenges in the application of randomized trials}},
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-}
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- title={When Texans Gerrymander: Much Power, Continuous Politics, Little Law}
-}
-
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- title={{Content Analysis: An Introduction to Its Methodology}},
- publisher={Thousand Oaks, CA: Sage},
- year={2004}
-}
-
- at article{Kruedener85,
- author={J{\"u}rgen von Kruedener},
- title={Die {\"U}berforderung der Weimarer Republic als Sozialstaat},
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- volume= 1,
- year= 1985,
- pages={358--376},
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-}
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- author={Anne O. Krueger},
- title={Government Failures in Development},
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- volume={4},
- year={1990},
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- number={3}
-}
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- author={Alan Krueger},
- title={Experimental Estimates of Education Production Functions},
- journal={Quarterly Journal of Economics},
- volume={114},
- year={1999},
- pages={497-532},
- month={May},
- number={2}
-}
-
- at article{KrzWys86,
- author={Mical Krzyzanowski and Miroslaw Wysocki},
- title={The Relation of Thirteen-Year Mortality to Ventilatory Impairment and Other
- Respiratory Symptoms: The Cracow Study},
- journal={International Journal of Epidemiology},
- volume= 15,
- year= 1986,
- pages={{56-64}},
- number= 1
-}
-
- at article{KucMwaLes06,
- author={Helmut K{\"u}chenohoff and Samuel M. Mwalili and Emmanuel Lassaffre},
- title={A General Method for Dealing with Misclassification in Regression: The Misclassification
- SIMEX},
- journal={Biometrics},
- volume={62},
- year={2006},
- pages={85-96},
- month={March}
-}
-
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- author={S. Kullback and R.A. Leibler},
- title={On Information and Sufficiency},
- journal={Annals of Mathematical Statistics},
- volume= 22,
- year= 1951,
- pages={79--86},
- month={March},
- number= 1
-}
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- at unpublished{KumAll04,
- author={Giridhar Kumaran and James Allan},
- title={Text Classification and Named Entities for New Event Detection},
- note={Center for Intelligent Information Retreival, Department of Computer Science,
- Univ of MA, Amherst},
- year={2004},
- month={July}
-}
-
- at unpublished{KumAll04,
- author={Giridhar Kumaran and James Allan},
- title={Text Classification and Named Entities for New Event Detection},
- note={Center for Intelligent Information Retreival, Department of Computer Science,
- Univ of MA, Amherst},
- year={2004},
- month={July}
-}
-
- at article{KunGeuvan95,
- author={Anton Kunst and J.J. Geurts and J. van den Berg},
- title={International variation in socioeconomic inequalities in self reported health},
- journal={Journal of Epidemiology and Community Health},
- year={1995},
- optnumber={2},
- optvolume={49},
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-}
-
- at article{KunGroMac98,
- author={A.E. Kunst and F. Gorenhof and J.P. Mackenbach and E.W. Health},
- title={Occupational class and cause specific mortality in middle aged men in 11
- European countries: comparison of population based studies. EU Working
- Group on Socioeconomic Inequalities in Health },
- journal= bmj,
- year={1998},
- optvolume={316},
- optpages={1636--1642}
-}
-
- at article{KunGroMac98b,
- author={Anton Kunst and F. Groenhof and Johann Mackenbach},
- title={Mortality by occupational class among men 30--64 years in 11 European countries},
- journal= ssm,
- volume= 46,
- year= 1998,
- pages={1459-1476},
- number= 11
-}
-
- at article{Kunsch87,
- author={Hans R. K{\"u}nsch},
- title={Intrinsic Autoregressions and Related Models on the Two-Dimensional Lattice},
- journal={Biometrika},
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- year= 1987,
- pages={517-524},
- number= 3
-}
-
- at article{Kuo01,
- author={Yen-Hong Kuo},
- title={Extrapolation of Association Between Two Variables in Four General Medical
- Journals},
- year= 2001 ,
- month={September},
- note={Forth International Congress on Peer Review in Biomedical Publication},
- key={Barcelona, Spain}
-}
-
- at book{kvart86,
- author={Igal Kvart},
- title={A Theory of Counterfactuals},
- publisher={Indianapolis: Hackett Publishing Company},
- year= 1986
-}
-
- at article{KwoShuHov06,
- author={Namhee Kwon and Stuart W. Shulman and Eduard Hovy},
- title={{Collective Text Analysis for eRulemaking}},
- journal={7th Annual International Conference on Digital Government Research},
- year={2006}
-}
-
- at incollection{LagRus02,
- author={Monica Lagazio and Bruce Russett},
- title={A Neural Network Analysis of Militarized International Disputes, 1885-1992:
- Temporal Stability and Causal Complexity},
- booktitle={The Scourge of War: New Extensions on an Old Problem},
- publisher={University of Michigan Press},
- year={2002},
- address={Ann Arbor},
- editor={Paul Diehl},
- optpages={269--295},
- optannote={This paper fits a model for Cold War militarized disputes and assess how
- well the Cold War model fits pre-Cold War data (so-called 'post-diction').
- So it gets fitted values. Also, runs test and training, and discusses merits
- of neural net approach.}
-}
-
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-}
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- author={Nan M. Laird and Thomas A. Louis},
- title={Empirical Bayes Confidence Intervals Based on Bootstrap Samples},
- journal={Journal of the American Statistical Association},
- volume={82},
- year={1987},
- pages={739-750},
- month={September},
- number={399}
-}
-
- at article{LaiLou87b,
- author={Nan M. Laird and Thomas A. Louis},
- title={Empirical Bayes Confidence Intervals Based on Bootstrap Samples: Rejoinder},
- journal={Journal of the American Statistical Association},
- volume={399},
- year={1987},
- pages={756-757},
- month={September}
-}
-
- at unpublished{Lakin05,
- author={Jason Lakin},
- title={Letting the Outsiders in: Democratization and Health Reform in Mexico},
- note={American Political Science Association},
- year= 2005 ,
- address={Washington D.C.}
-}
-
- at article{Lalonde86,
- author={Robert Lalonde},
- title={Evaluating the Econometric Evaluations of Training Programs},
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- volume={76},
- year={1986},
- pages={604-620}
-}
-
- at article{Landers05,
- author={John Landers},
- title={The Destructiveness of Pre-Industrial Warfare: Political and Technological
- Determinants},
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- volume={42},
- year={2005},
- pages={455-470},
- month={July},
- number={4}
-}
-
- at article{langholz91,
- author={B. Langholz and D.C. Thomas},
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-}
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- volume= 11,
- year= 1996,
- pages={35-53},
- number= 1
-}
-
- at article{langholz97,
- author={Bryan Langholz and Boran {\O }rnulf},
- title={Estimation of Absolute Risk from Nested Case-Control Data},
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- volume= 53,
- year= 1997,
- pages={767-774},
- month={June}
-}
-
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- author={Joseph LaPalombara},
- title={Macrotheories and Microapplications in Comparative Politics: A Widening
- Chasm},
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- month={October}
-}
-
- at book{Laplace1820,
- author={P.S. Laplace},
- title={Philosophical Essays on Probaiblities},
- publisher={Dover},
- year={1951, original: 1820},
- address={New York}
-}
-
- at article{LaRBanJar79,
- author={Asenath LaRue, PhD, Lew Bank, MA, Lissy Jarvick, MD, PhD, and Monte Hetland,
- BA},
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- volume= 34,
- year= 1979,
- pages={{687-91}}
-}
-
- at article{Lassen05,
- author={David Dreyer Lassen},
- title={The Effect of Information on Voter Turnout: Evidence from a Natural Experiement},
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- volume={2005},
- year={49},
- pages={103-118},
- month={January},
- number={1}
-}
-
- at article{Lau97,
- author={Tai-Shing Lau},
- title={The Latent Class Model for Multiple Binary Screening Tests},
- journal={Statistics in Medicine},
- volume={16},
- year={1997},
- pages={2283-2295}
-}
-
- at article{LauIbr95,
- author={Purushottam W. Laud and Joseph G. Ibrahim},
- title={Predictive Model Selection},
- journal= jrssb,
- volume= 57,
- year= 1995,
- pages={247--262},
- number= 1
-}
-
- at article{LauIbr96,
- author={Purushottam W. Laud and Joseph G. Ibrahim},
- title={Predictive Specification of Prior Model Probabilities in Variable Selection},
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- volume= 83,
- year= 1996,
- pages={267--274},
- number= 2
-}
-
- at article{LauSmiSta00,
- author={Jennifer L. Lauby and Philip J. Smith and Michael Stark and Bobbie Person
- and Janet Adams},
- title={A Community-Level HIV Prevention Intervention for Inner-City Women: Results
- of the Women and Infants Demonstration Projects},
- journal={American Journal of Public Health},
- volume={90},
- year={2000},
- pages={216-222},
- month={February},
- number={2}
-}
-
- at article{LavBenGar03,
- author={Michael Laver and Kenneth Benoit and John Garry},
- title={{Extracting Policy Positions from Political Texts Using Words as Data}},
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- volume={97},
- year={2003},
- pages={311-331},
- number={2}
-}
-
- at book{Leamer78,
- author={Edward Leamer},
- title={Specification Searches},
- publisher={Wiley},
- year= 1978,
- address={New York}
-}
-
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- pages={550--85},
- month={July}
-}
-
- at misc{Lechner00,
- author={Michael Lechner},
- title={A note on the common support problem in applied evaluation studies},
- year= 2000,
- howpublished={{http://www.siaw.unisg.ch/lechner}},
- note={University of St. Galen}
-}
-
- at incollection{Lechner99,
- author={Michael Lechner},
- title={Identification and Estimation of Causal Effects of Multiple Treatments under the Conditional Independence Assumption},
- booktitle={Econometric Evaluation of Labour Market Policies},
- publisher={Physica},
- address={Heidelberg},
- editor={Lechner, M. and Pfeiffer, F.},
- year= 2001,
- pages={43--58}
-}
-
-
-
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- and Applications},
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- volume= 4,
- year= 2000,
- pages={80--93},
- number= 1
-}
-
- at article{Lee00a,
- author={Ronald D. Lee},
- title={{Long-Term Projections and the US Social Security System}},
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- pages={137--143},
- month={March},
- number= 1
-}
-
- at article{Lee93,
- author={Ronald D. Lee},
- title={{Modeling and Forecasting the Time Series of US Fertility: Age Patterns,
- Range, and Ultimate Level}},
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- year= 1993,
- pages={187--202}
-}
-
-
- at article{LeeCar92,
- author = {Ronald D. Lee and Lawrence R. Carter},
- title = {{Modeling and Forecasting U.S. Mortality}},
- journal = jasa,
- volume = 87,
- year = 1992,
- month = {September},
- pages = {659--675},
- number = 419
-}
-
- at article{LeeCar92b,
- author={Ronald D. Lee and Lawrence R. Carter},
- title={Rejoinder},
- journal= jasa,
- volume= 87,
- year= 1992,
- pages={674--675},
- month={September},
- number= 419
-}
-
- at article{LeeCarTul95,
- author={Ronald D. Lee and Lawrence Carter and S. Tuljapurkar},
- title={Disaggregation in Population Forecasting: Do We Need It? And How to Do it
- Simply},
- journal={Mathematical Population Studies},
- volume={5},
- year={1995},
- pages={217--234},
- month={July},
- number={3},
- annote={Authors describe a model for reducing the dimensionality of the forecasting
- problem by modeling the evolution over time of the age schedules of vital
- rates, reducing the problem to forecasting a single parameter for fertility
- and another for mortality. Authors also show how one can fit the model
- more simply and prepare integrated forecasts for a collection of regions,
- and discuss alternate approaches to forecasting the estimated indices of
- fertility and mortality, including state-space methods.}
-}
-
- at misc{LeeHigBiFerWes00,
- author={Herbert Lee and David Higdon and Zhuoxin Bi and Marco Ferreira and Mike
- West},
- title={Markov Random Field Models for High-Dimensional Parameters in Simulations
- of Fluid Flow in Porous Media},
- year= 2000,
- howpublished={Discussion Paper \#00-35, Institute of Statistics and Decision Sciences,
- Duke University}
-}
-
- at book{LeeJohZel96,
- author={Jack C. Lee and Wesley O. Johnson and Arnold Zellner},
- title={Modelling and Prediction: Honoring Seymour Geisser},
- publisher={Springer},
- year={1996},
- editor={Jack C. Lee and Wesley O. Johnson and Arnold Zellner}
-}
-
- at article{LeeMil01,
- author={Ronald D. Lee and Timothy Miller},
- title={Evaluating the Performance of the Lee-Carter Approach to Modeling and Forecasting
- Mortality},
- journal={Demography},
- volume= 38,
- year= 2001,
- pages={537--549},
- month={November},
- number= 4
-}
-
- at article{LeeRof94,
- author={Ronald D. Lee and R. Rofman},
- title={Modeling and Projecting Mortality in Chile},
- journal={Notas Poblacion},
- volume={22},
- year={1994},
- pages={183--213},
- month={Jun},
- number={59},
- annote={Authors extend the Lee-Carter method to deal with various problems of incomplete
- data common in Third World populations, and then apply the method to forecast
- mortality in Chile.}
-}
-
- at article{LeeSki99,
- author={Ronald D. Lee and Jonathan Skinner},
- title={Will Aging Baby Boomers Bust the Federal Budget},
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- volume= 13,
- year= 1999,
- pages={117--140},
- month={Winter},
- number= 1
-}
-
- at article{LeeTul94,
- author={Ronald D. Lee and S. Tuljapurkar},
- title={{Stochastic Population Projections for the U.S.: Beyond High, Medium and
- Low}},
- journal= jasa,
- volume= 89,
- year= 1994,
- pages={1175--1189},
- month={December},
- number= 428
-}
-
- at article{LeeTul98,
- author={Ronald D. Lee and S. Tuljapurkar},
- title={{Uncertain Demographic Futures and Social Security Finances}},
- journal={American Economic Review: Papers and Proceedings},
- year= 1998,
- pages={237--241},
- month={May}
-}
-
- at incollection{LeeTul98a,
- author={Ronald D. Lee and S. Tuljapurkar},
- title={{Stochastic Forecasts for Social Security}},
- booktitle={Frontiers in the Economics of Aging},
- publisher={University of Chicago Press},
- year= 1998,
- address={Chicago},
- editor={David Wise},
- pages={393--420}
-}
-
- at techreport{LenFox06,
- author={Amanda Lenhart and Susannah Fox},
- title={{Bloggers: A Portrait of the Internet's New Storytellers}},
- institution={Pew Internet and American Life Project},
- year= 2006,
- note={{http://207.21.232.103/pdfs/PIP\%20Bloggers\%20Report\%20July\%2019\%202006.pdf}}
-}
-
- at book{LenHsu99,
- author={T. Leonard and J.S.J. Hsu},
- title={Bayesian Methods},
- publisher={Cambridge University Press},
- year= 1999,
- address={Cambridge}
-}
-
- at unpublished{LeuSia03,
- author={E. Leuven and B. Sianesi},
- title={psmatch2},
- note={{Stata module to perform full {M}ahalanobis and propensity score matching,
- common support graphing, and covariate imbalance testing. Available at:
- http://www1.fee.uva.nl/scholar/mdw/leuven/stata}},
- year= 2003
-}
-
- at misc{LeuSia04,
- author={Edwin Leuven and Barbara Sianesi},
- title={PSMATCH2: Stata module to perform full Mahalanobis and propensity score
- matching, common support graphing, and covariate imbalance testing},
- year= 2004,
- howpublished={EconPapers},
- note={{http://econpapers.repec.org/software/bocbocode/S432001.htm}}
-}
-
- at article{LeuTanLue97,
- author={Kai-Kuen Leung, Li-Yu Tang, and Bee-Horng Lue},
- title={Self-Rated Health and Mortality in Chinese Institutional Elderly Persons},
- journal={Journal of Clinical Epidemiology},
- volume= 50,
- year= 1997,
- pages={{1107-16}},
- number= 10
-}
-
- at book{Levinson01,
- author={Sanford Levinson},
- title={What is the Constitution's Role in Wartime: Why Free Speech and Other Rights
- Are Not as Safe as You Might Think},
- publisher={?},
- year= 2001
-}
-
- at article{LevKas70,
- author={P.S. Levy and E. H. Kass},
- title={A three population model for sequential screening for Bacteriuria},
- journal={American Journal of Epidemiology},
- volume={91},
- year={1970},
- pages={148-154}
-}
-
- at article{Lewis01,
- author={Jeffrey B. Lewis},
- title={Estimating Voter Preference Distributions from Individual-Level Voting Data},
- journal={Political Analysis},
- volume= 9,
- year= 2001,
- pages={275-297},
- month={June},
- number= 3
-}
-
- at article{Lewis03,
- author={Anthony Lewis},
- title={Marbury v. Madison v. Ashcroft},
- journal={New York Times},
- year={2003},
- month={February 24, A17}
-}
-
- at incollection{Lewis05,
- author={Maureen Lewis},
- title={Improving Efficiency and Impact in Health Care Services: Lessons from Central
- America},
- booktitle={Health Systems Innovation in Central America},
- publisher={The World Bank},
- year= 2005,
- address={Washington, D.C.},
- editor={Gerard M. La Forgia}
-}
-
- at inbook{Lewis05,
- author={Maureen Lewis},
- title={Health Sysems Innovatin in Central American},
- chapter={Improving Efficiency and Impact in Health Care Services - Lessons from Central
- American },
- year={2005},
- publisher={The World Bank},
- address={Washington DC},
- editor={Gerard M. La Forgia}
-}
-
- at book{lewis73,
- author={David K. Lewis},
- title={Counterfactuals},
- publisher={Cambridge: Harvard University Press},
- year= 1973
-}
-
- at article{Lewis99b,
- author={John A. Lewis},
- title={Statistical Principles for Clinical Trials (ICH E9) An Introductory Note
- on an International Guideline},
- journal={Statistics in Medicine},
- volume={18},
- year={1999},
- pages={1903-1904}
-}
-
- at article{LewLev89,
- author={R.A. Lew and P.S. Levy},
- title={Estimation of prevalence on the basis of screening tests},
- journal={Statistics in Medicine},
- volume={8},
- year={1989}
-}
-
- at article{LewLev89,
- author={Robert A. Lew and Paul S. Levy},
- title={Estimation of Prevalence on the Basis of Screening Tests},
- journal={Statistics in Medicine},
- volume={8},
- year={1989},
- pages={1225-1230}
-}
-
- at book{Li95,
- author={S.Z. Li},
- title={Markov Random Field Modeling in Computer Vision},
- publisher={Springer-Verlag},
- year= 1995
-}
-
- at article{LicLipDan92,
- author={Allen S. Lichter and Marc E. Lippman and David N. Danforth Jr and Teresa
- d'Angelo and Seth M. Steinberg and Ernest deMoss and Harold D. MacDonald
- and Cheryl M. Reichert and Maria Merino and Sandra M. Swain and Kenneth
- Cowan and Lynn H. Gerber and Judith L. Bader and Peggie A. Findlay and
- Wendy Schain and Catherine R. Gorrell and Karen Straus and Steven A. Rosenberg
- and Eli Glatstein},
- title={Mastectomy Versus Breast-Conserving Therapy in the Treatment of Stage I
- and II Carcinoma of the Breast: A Randomized Trial at the National Cancer
- Institute},
- journal={Journal of Clinical Oncology},
- volume= 10,
- year= 1992,
- pages={976-983},
- month= June ,
- number= 6
-}
-
- at article{LilPer94,
- author={David E. Lilienfeld and Daniel P. Perl},
- title={Projected Neurodegenerative Disease Mortality among Minorities in the United
- States},
- journal={Neuroepidemiology},
- volume= 13,
- year= 1994,
- pages={179--186}
-}
-
- at article{LinCutZwi02,
- author={Shin Lin and David L. Cutler and Michael E. Zwick and Aravinda Chakravarti},
- title={Haplotype Inference in Random Population Samples},
- journal={American Journal of Human Genetics},
- volume= 71,
- year= 2002,
- pages={1129--1137}
-}
-
- at book{LinHam97,
- title={Handbook of Modern Item Response Theory},
- publisher={Springer},
- year= 1997,
- editor={Wim Van Der Linden and Ronald K. Hambleton},
- address={New York}
-}
-
- at article{LinLin80,
- author={Bernard S. Linn and Margaret W. Linn},
- title={Objective and self-assessed health in the old and very old},
- journal={Social Science and Medicine },
- volume={{14A}},
- year= 1980,
- pages={{311-15}}
-}
-
- at article{LinPekWan05,
- author={Peter K. Lindenauer and Penelope Pekow and Kaijun Wang and Dheeresh K. Mamidi
- and Benjamin Guierrez and Evan M. Benjamin},
- title={Perioperative beta-blocker therapy and mortality after major noncardiac
- surgery},
- journal={New England Journal of Medicine},
- volume={353},
- year={2005},
- pages={349-361},
- month={July},
- number={4}
-}
-
- at article{LinSmi72,
- author={D. V. Lindley and A. F. M. Smith},
- title={{B}ayes Estimates for the Linear Model},
- journal={Journal of the Royal Statistical Society B},
- volume= 34,
- year= 1972,
- pages={1-41},
- number= 1
-}
-
- at book{Lipset63,
- author={Lipset, Seymour Martin},
- title={Political Man: The Social Basis of Politics},
- publisher={Anchor Books},
- year= 1963,
- address={Garden City, NY}
-}
-
- at article{LisMilFre03,
- author={John A. List and Daniel L. Millimet and Per G. Fredriksson and W. Warren
- McHone},
- title={Effects of Environmental Regulations on Manufacturing Plant Births: Evidence
- from a Propensity Score Matching Estimator},
- journal={The Review of Economics and Statistics},
- volume={85},
- year={2003},
- pages={944-952},
- month={November},
- number={4}
-}
-
- at article{LitAn04,
- author={Roderick Little and Hyonggin An},
- title={Robust Likelihood-Based Analysis of Multivariate Data with Missing Values},
- journal={Statistica Sinica},
- volume={14},
- year={2004},
- pages={949-968}
-}
-
- at article{LitAn04,
- author={Roderick Little and Hyonggin An},
- title={Robust Likelihood-Based Analysis of Multivariate Data with Missing Values},
- journal={Statistica Sinica},
- volume={14},
- year={2004},
- pages={949-968}
-}
-
- at book{LitRub02,
- author={Roderick J.A. Little and Donald B. Rubin},
- title={Statistical Analysis with Missing Data, 2nd Edition},
- publisher={John Wiley and Sons},
- year={2002},
- address={New York, New York}
-}
-
- at article{LitRub89,
- author={Rodrick J. Little and Donald Rubin},
- title={The Analysis of Social Science Data with Missing Values},
- journal={Sociological Methods and Research},
- volume={18},
- year={1989},
- pages={292-326}
-}
-
- at inbook{LitSch95,
- author={Rodrick J. Little and N. Schenker},
- title={Handbook of Statistical Modeling for the Social and Behavioral Sciences},
- chapter={Missing Data},
- year={1995},
- pages={39-75}
-}
-
- at unpublished{Little05,
- author={Roderick Little},
- title={Calibrated Bayes: A Bayes/Frequentist Roadmap},
- note={University of Michigan},
- year={2005},
- month={September}
-}
-
- at article{Little92,
- author={Roderick J. Little},
- title={Regression with Missing X's: A Review},
- journal={Journal of the American Statistical Association},
- volume={87},
- year={1992},
- pages={1227-1237}
-}
-
- at unpublished{LiuHuChe05,
- author={Bing Liu and Minqing Hu and Junsheng Cheng},
- title={Opinion Observer: Analyzing and Comparing Opinions on the Web},
- note={Bing Liu Dept of Computer Science; Univ of Illinois at Chicago, 851 south
- Morgan St. Chicago, IL 60607-7053, liub at cs.uic.edu},
- year={2005},
- month={May}
-}
-
- at article{LiuWonKon94,
- author={J. Liu and W.H. Wong and A. Kong},
- title={Covariance Structure of the Gibbs Sampler with Applications to the Comparisons
- of Estimators and Augmentation Schemes},
- journal={Biometrika},
- volume={81},
- year={1994},
- pages={27-40}
-}
-
- at article{LiWen05,
- author={Quan Li and Ming Wen},
- title={The Immediate and Lingering Effects of Armed Conflict on Adult Mortality:
- A Time-Series Cross-National Analysis},
- abstract={This research investigates the effect of armed conflict on adult mortality
- across countries and over time. Theoretical mechanisms are specified for
- how military violence influences adult mortality, both immediately and
- over time after conflict. The effects of aggregate conflict, interstate
- and intrastate conflicts, and conflict severity are explored. The Heckman
- selection model is applied to account for the conflict-induced missing
- data problem. A pooled analysis across 84 countries for the period from
- 1961 to 1998 provides broad empirical support for the proposed theoretical
- expectations across both genders. This study confirms the importance of
- both the immediate and the lingering effect of military conflict on the
- mortality of the working-age population. The immediate effect of civil
- conflict is much stronger than that of the interstate conflict, while the
- reverse applies to the lingering effect. Both the immediate and the lingering
- effects of severe conflict are much stronger than those of minor conflict.
- While men tend to suffer higher mortality immediately from intrastate conflict
- and severe conflict, women in the long run experience as much mortality
- owing to the lingering effects of these conflicts. The mortality data show
- a strong data selection bias caused by military conflict. The research
- findings highlight the imperative for negotiating peace. Preventing a contest
- from escalating into a severe conflict can produce noticeable gains in
- saved human lives.},
- journal={Journal of Peace Research},
- volume={42},
- year={2005},
- pages={471-492},
- month={July},
- number={4}
-}
-
- at article{LoeFulKag03,
- author={Susanna Loeb and Bruce Fuller and Sharon Lynn Kagan and Bidemi Carrol},
- title={How Welfare Reform Affects Young Children: Experimental Findings from Connecticut
- - A Research Note},
- journal={Journal of Policy Analysis and Management},
- volume={22},
- year={2003},
- pages={537-550},
- number={4}
-}
-
- at article{Londregan00,
- author={John Londregan},
- title={Estimating Legislator's Preferred Points},
- journal={Political Analysis},
- volume= 8,
- year= 2000,
- pages={21--34},
- month={Winter},
- number= 1
-}
-
- at book{Londregan00b,
- author={John Londregan},
- title={Legislative Institutions and Ideology in Chile},
- publisher={Cambridge University Press},
- year= 2000,
- address={New York}
-}
-
- at book{LonFre06,
- author={J. Scott Long and Jeremy Freese},
- title={Regression Models for Categorical Dependent Variables Using Stata},
- publisher={Stata Press},
- year={2006},
- address={College Station, TX}
-}
-
- at article{LooBee46,
- author={Loomis, C. P. and Beegle, J. A.},
- title={The Spread of German Nazism in Rural Areas},
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- volume= 11,
- year= 1946,
- pages={724-734}
-}
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- at book{LopAhmGui00,
- author = {Alan Lopez and O. Ahmed and M. Guillot and
- B.D. Ferguson and J.A. Salomon and C.J.L. Murray and
- K.H. Hill},
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- Countries},
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- year = 2000,
- address = {Geneva}
-}
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- at article{LowAltFer98,
- author={Robert Lowry and James E. Alt and Karen Ferree},
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- pages={759-777},
- month={December}
-}
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- at article{Lowenstein2006,
- author={Daniel H. Lowenstein},
- title={Vieth's Gap: Has the Supreme Court Gone from Bad to Worse on Partisan Gerrymandering?},
- journal={Cornell Journal of Law and Public Policy},
- volume={N:X},
- year={2006},
- pages={101-130},
- month={January}
-}
-
- at article{LozSolGak06,
- author = {Rafael Lozano and Patricia Soliz and Emmanuela
- Gakidou and Jesse Abbott-Klafter and Dennis
- M. Feehan and Cecilia Vidal and Juan Pablo Ortiz and
- Christopher J.L. Murray},
- title = {Benchmarking of performance of Mexican States with
- Effective Coverage},
- journal = {The Lancet},
- volume = {368},
- year = {2006},
- pages = {1729-1741},
- month = {November}
-}
-
- at article{lubin94,
- author = {J.H. Lubin and M.H. Gail},
- title = {Sampling Strategies in Nested Case-Control Studies},
- journal = {Environmental Health Perspectives},
- volume = 102,
- year = 1994,
- pages = {47-51},
- number = {suppl 8}
-}
-
- at article{Lubkemann05,
- author = {Stephen C. Lubkemann},
- title = {Migratory Coping in Wartime Mozambique: An
- Anthropology of Violence and Displacement in
- Fragmented Wars},
- journal = {Journal of Peace Research},
- volume = {42},
- year = {2005},
- pages = {493-508},
- month = {July},
- number = {4}
-}
-
- at article{LumHea99,
- author = {Thomas Lumley and Patrick Heagerty},
- title = {Weighted Empirical Adaptive Variance Estimators for
- Correlated Data Regression},
- journal = {jrssb},
- volume = {61},
- year = {1999},
- pages = {459--477},
- number = {2}
-}
-
- at article{LunSmi05,
- author = {Jennifer Hickes Lundquist and Herbert L. Smith},
- title = {Family Formation Among Women in the U.S. Military:
- Evidence from the NLSY},
- journal = {Journal of Marriage and Family},
- volume = {67},
- year = {2005},
- pages = {1-13},
- month = {February}
-}
-
- at article{LuRos04,
- author={Bo Lu and Paul R. Rosenbaum},
- title={Optimal Pair Matching With Two Control Groups},
- journal={Journal of Computational and Graphical Statistics},
- volume={13},
- year={2004},
- pages={422-434},
- number={2}
-}
-
- at inbook{Lustig94,
- author={Nora Lustig},
- title={Solidarity as a Strategy of Poverty Alleviation},
- chapter={5},
- year={1994},
- publisher={Center for U.S.-Mexican Studies},
- pages={79-96},
- series={U.S.-Mexico Contemporary Perspectives Series, 6},
- address={University of California, San Diego}
-}
-
- at article{LuZanHor01,
- author = {Bo Lu and Elaine Zanuto and Robert Hornik and Paul
- R. Rosenbaum},
- title = {Matching With Doses in an Observational Study of a
- Media Campaign Against Drug Abuse},
- journal = {Journal of the American Statistical Association},
- volume = {96},
- year = {2001},
- pages = {1245-1253},
- month = {December},
- number = {456}
-}
-
- at techreport{LymVar03,
- author = {Peter Lyman and Hal R. Varian},
- title = {{How much information 2003}},
- institution = {University of California},
- year = 2003,
- note =
- {{http://www2.sims.berkeley.edu/research/projects/how-much-info-2003/}}
-}
-
- at article{Lynch03,
- author = {Lynch, C.A.},
- title = {{Institutional Repositories: Essential
- Infrastructure For Scholarship In The Digital Age}},
- journal = {portal: Libraries and the Academy},
- volume = {3},
- year = {2003},
- pages = {327--336},
- number = {2}
-}
-
- at article{LynMcc92,
- author = {Henry S. Lynn and Charles E. McCulloch},
- title = {When Does it Pay to Break the Matches for Analysis
- of a Matched-Pairs Design?},
- journal = {Biometrics},
- volume = {48},
- year = {1992},
- pages = {397-409},
- month = {June}
-}
-
- at article{MacKunGro99,
- author = {J.P. Mackenbach and A.E. Kunst and F. Groenhof and
- J.K. Borgan and G. Costa and F. Faggiano },
- title = {Socioeconomic inequalities in mortality among women
- and among men: an international study},
- journal = {American Journal of Public Health},
- volume = 89,
- year = 1999,
- pages = {1800-1806},
- number = 12
-}
-
- at book{Macridis55,
- author={Roy C. Macridis},
- title={The Study of Comparative Government},
- publisher={Doubleday and Co.},
- year= 1955,
- address={New York}
-}
-
- at article{MacRivJur06,
- author = {Ellen J. MacKenzie and Frederick P. Rivara and
- Gregory J. Jurkovich and Avery B. Nathens and
- Katherine P. Frey and Brian L. Egleston and David
- S. Salkever and Daniel O Scharfstein},
- title = {A National Evaluation of the Effect of Trauma-Center
- Care on Mortality},
- journal = {New England Journal of Medicine},
- volume = {354},
- year = {2006},
- pages = {366-378},
- month = {January}
-}
-
- at article{MadDou64,
- author = {George L. Maddox and Elizabeth B. Douglas},
- title = {Self-Assessments of Health: A Longitudinal Study of
- Elderly Subjects},
- journal = {Journal of Health and Social Behavior },
- volume = 14,
- year = 1973,
- pages = {{87-93}}
-}
-
- at article{MadNel92,
- author = {W.R. Madych and S.A. Nelson},
- title = {Bounds on Multivariate Polynomials and Exponential
- Error Estimates for Multiquadric Interpolation},
- journal = {Journal of Approximation Theory},
- volume = 70,
- year = 1992,
- pages = {94--114}
-}
-
- at article{Malaker86,
- author={CR Malaker},
- title={Estimation of Adult Mortality in India: 1971--1981},
- journal={Demography India},
- volume= 15,
- year= 1986,
- pages={126--136}
-}
-
- at article{ManKarMar03,
- author = {Kristiina Manderbacka, et al},
- title = {The Effect of Point of Reference on the Association
- Between Self-Rated Health and Mortality},
- journal = {Social Science and Medicine},
- volume = 56,
- year = 2003,
- pages = {{1447-52}}
-}
-
- at book{ManSch99,
- author={Christopher D. Manning and Hinrich Sch{\"u}tze},
- title={Foundations of Statistical Natural Language Processing},
- publisher={Massachusetts Institute of Technology},
- year={1999},
- address={Cambridge, MA}
-}
-
- at book{Manski05,
- author={Charles F. Manski},
- title={Social choice with Partial Knowledge of Treatment Response},
- publisher={Princeton University Press},
- year={2005},
- series={Econometric Institute Lectures}
-}
-
- at article{Manski77,
- author={Charles F. Manski},
- title={The Estimation of Choice Probabilities from Choice Based Samples},
- journal={Econometrics},
- volume= 45,
- year= 1977,
- pages={1977--88},
- month={November},
- number= 8
-}
-
- at article{Manski90,
- author = {Charles F. Manski},
- title = {The Use of Intentions Data to Predict Behavior: A
- Best-Case Analysis},
- journal = {Journal of the American Statistical Association},
- volume = {85},
- year = {1990},
- pages = {934-940},
- month = {December},
- number = {412}
-}
-
- at book{Manski95,
- author={Charles F. Manski},
- title={Identification Problems in the Social Sciences},
- publisher={Harvard University Press},
- year= 1995
-}
-
- at inproceedings{manski99,
- author = {Charles F. Manski},
- title = {Nonlinear Statistical Inference: Essays in Honor of
- Takeshi Amemiya},
- booktitle = {Nonparametric Identification Under Response-Based
- Sampling},
- year = 1999 ,
- publisher = cup,
- editor = {C. Hsiao and K. Morimune and J. Powell}
-}
-
- at article{ManSzoKoh01,
- author = {Mandl, K.D. and Szolovits, P. and Kohane, I.S.},
- title = {{Public standards and patients' control: how to keep
- electronic medical records accessible but private}},
- journal = {BMJ},
- volume = {322},
- year = {2001},
- pages = {283--7},
- number = {7281}
-}
-
- at article{ManSzoKoh01,
- author={Kenneth D. Mandl and Peter Szolovits and Isaac S. Kohane},
- title={Public standards and patients' control: how to keep electronic medical records
- accessible but private},
- journal={British Medical Journal},
- volume={322},
- year={2001},
- pages={283-287},
- month={February},
- publisher={British Medical Journal}
-}
-
- at article{mantel73,
- author={N. Mantel},
- title={Synthetic Retrospective Studies and Related Topics},
- journal={Biometrics},
- volume= 29,
- year= 1973,
- number={479-486}
-}
-
-
- at article{ManTudDie06,
- author={Dennis T. Mangano and Julia C. Tudor and Cynthia Dietzel},
- title={The Risk Associated wtih Aprotinin in Cardiac Surgery},
- journal={The New England Journal of Medicine},
- volume={354},
- year={2006},
- pages={353-365},
- month={January},
- number={4}
-}
-
- at article{ManRao04,
- title = {{Community-Based and-Driven Development: A Critical
- Review}},
- author = {Mansuri, G. and Rao, V.},
- journal = {The World Bank Research Observer},
- volume = {19},
- number = {1},
- pages = {1-39},
- year = {2004}
-}
-
- at article{MarCamFay91,
- author = {Elizabeth A. Martin and Pamela C. Campanelli and
- Robert E. Fay},
- title = {An Application of Rasch Analysis to Questionnaire
- Design: Using Vignettes to Study the Meaning of
- `Work' in the Current Population Survey},
- journal = {The Statistician},
- volume = 40,
- year = 1991,
- pages = {265--276},
- month = {September},
- number = 3
-}
-
- at article{March57,
- author={James G. March},
- title={party Legislative Representation as a Function of Election Results},
- journal={1957},
- volume={21},
- year={1957-1958},
- pages={521-542},
- month={Winter},
- number={4}
-}
-
- at article{Marcus00,
- author={George E. Marcus},
- title={{Emotions in Politics}},
- journal={Annual Review of Political Science},
- volume={3},
- year={2006},
- pages={221-50}
-}
-
- at article{Marcus88,
- author={George E. Marcus},
- title={{The Structure of Emotional Response: The 1984 Presidential Candidates}},
- journal={American Political Science Review},
- volume={82},
- year={1988},
- pages={737-761},
- number={3}
-}
-
- at article{MarDiePer93,
- author={Donald C. Martin and Paula Diehr and Edward B. Perrin and Thomas D. Koepsell},
- title={The Effect of Matching on the Power of Randomized Community Intervention
- Studies},
- journal={Statistics in Medicine},
- volume={12},
- year={1993},
- pages={329-338}
-}
-
- at article{MarHusLob95,
- author={David Marsh and Khatidja Husein and Melvyn Lobo and Mehboob Ali Shah and
- Stephen Luby},
- title={Verbal autopsy in Karachi slums: comparing single and multiple cause of
- child deaths},
- journal={Health Policy and Planning},
- volume={10},
- year={1995},
- pages={395-403},
- number={4}
-}
-
- at article{MarHusLob95,
- author={David Marsh and Khatidja Husein and Melvyn Lobo and Mehboob Ali Shah and
- Stephen Luby},
- title={Verbal autopsy in Karachi slums: comparing single and multiple cause of
- child deaths},
- journal={Health Policy and Planning},
- volume={10},
- year={1995},
- pages={395-403},
- number={4}
-}
-
- at book{MarKenBib79,
- author={K. V. Mardia and J. T. Kent and J. M. Bibby},
- title={Multivariate Analysis},
- publisher= ap,
- year={1979},
- address={London}
-}
-
- at article{MarMajRas93,
- author={David Marsh and Nuzhat Majit and Zeba Rasmussen and Khalid Mateen and Arif
- Amin Khan},
- title={Cause-Specific Child Mortality In A Mountainous Community In Pakistan By
- Verbal Autopsy},
- journal={Journal of the Pakistan Medical Association},
- volume={43},
- year={1993},
- pages={226-229},
- month={November},
- number={11}
-}
-
- at article{MarMajRas93,
- author={David Marsh and Nuzhat Majit and Zeba Rasmussen and Khalid Mateen and Arif
- Amin Khan},
- title={Cause-Specific Child Mortality In A Mountainous Community In Pakistan By
- Verbal Autopsy},
- journal={Journal of the Pakistan Medical Association},
- volume={43},
- year={1993},
- pages={226-229},
- month={November},
- number={11}
-}
-
- at misc{MarQui01,
- author={Andrew D. Martin and Kevin M. Quinn},
- title={The Dimensions of {S}upreme {C}ourt Decision Making: Again Revisiting {T}he
- {J}udicial {M}ind},
- year= 2001,
- howpublished={Paper presented at the Annual Meeting of the Midwest Political Science Association}
-}
-
- at manual{MarQui05,
- author={Andrew D. Martin and Kevin M. Quinn},
- title={MCMCpack: Markov chain Monte Carlo (MCMC) Package},
- year={2005},
- url={{http://mcmcpack.wustl.edu}}
-}
-
- at article{MarSadFik03,
- author={David R. Marsh and Salim Sadruddin and Fariyal F. Fikree and Chitra Krishnan
- and Gary L. Darmstadt},
- title={Validation of verbal autopsy to determine the cause of 137 neonatal deaths
- in Karachi, Pakistan},
- journal={2003},
- volume={17},
- year={2003},
- pages={132-142}
-}
-
- at article{MarSadFik03,
- author={David R. Marsh and Salim Sadruddin and Fariyal F. Fikree and Chitra Krishnan
- and Gary L. Darmstadt},
- title={Validation of verbal autopsy to determine the cause of 137 neonatal deaths
- in Karachi, Pakistan},
- journal={2003},
- volume={17},
- year={2003},
- pages={132-142}
-}
-
- at article{Marshall91,
- author={R.J. Marshall},
- title={Mapping Disease and Mortality Rates using Empirical Bayes Estimators},
- journal={Applied Statistics},
- volume= 40,
- year= 1991,
- pages={283--294},
- number= 2
-}
-
- at article{MarSmiSta91,
- author={M.G. Marmot and G.D. Smith and S. Stansfeld and C. Patel and F. North and
- J. Head and I. White and E. Brunner and A. Feeney},
- title={Health inequalities among British civil servants: the Whitehall II study
- [see comments].},
- journal= lan,
- year={1991},
- optvolume={337},
- optpages={1387--1393}
-}
-
- at book{Martin92,
- author={Lisa Martin},
- title={Coercive Cooperation: Explaining Multilateral Economic Sanctions},
- publisher={Princeton University Press},
- year={1992},
- note={Please inquire with Lisa Martin before publishing results from these data,
- as this dataset includes errors that have since been corrected.}
-}
-
- at article{MatFatIno05,
- author = {Colin D. Mathers and Doris Ma Fat and Mie Inoue and
- Chalapati Rao and Alan Lopez},
- title = {Counting the dead and what they died from: an
- assessment of the global status of cause of death
- data},
- journal = {Bulletin of the World Health Organization},
- volume = 83,
- year = 2005,
- pages = {171--177},
- month = {March},
- number = 3
-}
-
- at unpublished{MatLopSte03,
- author={Colin D. Mathers and Alan Lopez and Claudia Stein and Doris Ma Fat and Chalapati
- Rao and Mie Unoue and Kenji Shiubuya and Niels Tomijima and Christina Bernard
- and Hongyi Xu},
- title={Deaths and Disease Burden by Cause: Global Burden of Disease Estimates for
- 2001 by World Bank Country Groups},
- note={Evidence and Information for Policy, World Health Organization, Geneva and
- School of Population health, University of Queensland, Brisbane, Austrailia},
- year={2003}
-}
-
- at unpublished{MatSteFat02,
- author={Colin D. Mathers and Claudia Stein and Doris Ma Fat and Chalapati Rao and
- Mie Unoue and Niels Tomijima and Christina Bernard and Alan D. Lopez and
- Christopher J.L. Murray},
- title={Global Burden of Disease 2000: Version 2 Methods and Results},
- note={Global Programme on Evidence for Health Policy Discussion Paper No. 50 World
- Health Organization},
- year={2002},
- month={October}
-}
-
- at article{MauRos97,
- author={Gillian H. Maude and David A. Ross},
- title={The Effect of Different Sensitivity, Specificity and Cause-Specific Mortality
- Fractions on the Estimation of Differences in Cause-Specific Mortality
- Rates in Children from Studies Using Verbal Autopsies},
- journal={International Journal of Epidemiology},
- volume={26},
- year={1997},
- pages={1097-1106},
- number={5}
-}
-
- at techreport{Mayaud01,
- author={Philippe Mayaud},
- title={Aids-Related Research Projects},
- institution={The London School of Hygiene \& Tropical Medicine},
- year={2001},
- address={London School of Hygiene \& Tropical Medicine www.ishtm.ac.uk}
-}
-
- at book{McCNel89,
- author={Peter McCullagh and James A. Nelder},
- title={Generalized Linear Models},
- publisher={Chapman \& Hall},
- year={1989},
- series={Monograph on Statistics and Applied Probability},
- edition={2nd},
- number={37}
-}
-
- at inbook{McConahay86,
- author={John B. McConahay},
- title={Prejudice, Discrimination, and Racism: Theory and Research},
- chapter={Modern Racism Ambivalence, and the Modern Racism Scale},
- year={1986},
- publisher={New York: Academic Press},
- editor={J. Dovidio and S.L. Gaertner}
-}
-
- at article{MccRidMor04,
- author={Daniel F. McCaffrey and Greg Ridgeway and Andrew R. Morral},
- title={Propensity Score Estimation With Boosted Regression for Evaluating Causal
- Effects in Observational Studies},
- journal={Psychological Methods},
- volume={9},
- year={2004},
- pages={403-425},
- number={4}
-}
-
- at article{McCShaWan94,
- author={John McCallum, DPhil, MPhil, Bruce Shadbolt, PhD, and Dong Wang, BSc},
- title={Self-Rated Health and Survival: A 7-year Follow-Up study of Australian Elderly.},
- journal={American Journal of Public Health},
- volume= 84,
- year= 1994,
- pages={{1100-05}}
-}
-
- at unpublished{McDonald06a,
- author={Michael P. McDonald},
- title={Seats to Votes Ratios in the United States},
- note={George Mason University, Dept of Public and International Affairs 4400 University
- Dr., 3-F4 Fairfax, VA 22030-4444 (703)-993-4191 mmcdon at gmu.edu},
- year={2006}
-}
-
- at unpublished{McDonald06b,
- author={Michael D. McDonald},
- title={A Standard for Detecting and Remedying Gerrymanders},
- note={Department of Political Science, Binghamton University- SUNY, Binghamton
- NY 13902-6000, (617) 777-2946, mdmcd at binghamton.edu},
- year={2006}
-}
-
- at article{McKibbin69,
- author={Ross McKibbin},
- title={The Myth of the Unemployed: Who did Vote for the Nazis?},
- journal={Australian Journal of Politics and History},
- volume= 15,
- year= 1969,
- pages={25--40},
- number= 2
-}
-
- at book{McLThr97,
- author={Geoffrey J. McLachlan and Thriyambakam Krishan},
- title={The EM Algorithm and Extensions},
- publisher={New York: Wiley}
-}
-
- at article{McNown92,
- author={Robert McNown},
- title={Comment},
- journal= jasa,
- volume= 87,
- year= 1992,
- pages={671--672},
- number= 419
-}
-
- at article{McNRog89,
- author={Rober McNown and Andrei Rogers},
- title={Forecasting Mortality: A Parameterized Time Series Approach},
- journal={Demography},
- volume= 26,
- year= 1989,
- pages={645--660},
- number= 4
-}
-
- at article{McNRog92,
- author={Robert McNown and Andrei Rogers},
- title={Forecasting Cause-Specific Mortality Using Time Series Methods},
- journal={International Journal of Forecasting},
- volume= 8,
- year= 1992,
- pages={413--432}
-}
-
- at unpublished{McqLasLai06,
- author={Matthew B. McQueen and Jessica Lasky-Su and Nan M. Laird and Christoph Lange},
- title={Screening and Testing using the Same Data Set: A Testing Strategy for Genome-Wide
- Association Studies for Case-Control and Case-Cohort Designs},
- year={2006}
-}
-
- at article{Mead92,
- author={A. Mead},
- title={Review of the Development of Multidimensional Scaling Methods},
- journal={The Statistician},
- volume= 41,
- year= 1992,
- pages={27--39},
- month={April},
- number= 1
-}
-
- at article{MebSek04,
- author={Walter Mebane and Jasjeet Sekhon},
- title={Robust Estimation and Outlier Detection in Overdispersed Multinomial Models
- of Count Data},
- journal= ajps,
- volume= 48,
- year= 2004,
- pages={391--410},
- month={April}
-}
-
- at article{MeiKarPar04,
- author={Bettina Meinow et al.},
- title={The effect of the duration of follow-up in mortality analysis: The temporal
- pattern of different predictors},
- journal={Journal of Gerontology: Social Sciences},
- volume={{59B}},
- year={2004},
- pages={{S181-89}},
- number={3}
-}
-
- at article{Meng94,
- author={Xiao-Li Meng},
- title={Multiple-Imputation Inferences with Uncongenial Sources of input},
- journal={Statistical Science},
- volume={9},
- year={1994},
- pages={538-573},
- number={4}
-}
-
- at article{Meng94b,
- author={X.L. Meng},
- title={Posterior Predictive p-Values},
- journal={Annals of Statistics},
- volume={22},
- year={1994},
- pages={1142-1160},
- number={3}
-}
-
- at article{MenRom03,
- author={Xiao-Li Meng and Marin Romero},
- title={Discussion: Efficiency and Self-Efficiency with Multiple Imputation Inference},
- journal={International Statistical Review},
- volume={71},
- year={2003},
- pages={607-618},
- number={3}
-}
-
- at article{MenRub92,
- author={X.L. Meng and Donald Rubin},
- title={Performing Likelihood Ratio Tests with Multiply-imputed Data Sets},
- journal={Biometrika},
- volume={79},
- year={192},
- pages={103-111}
-}
-
- at article{Metetal53,
- author={N. Metropolis and A. W. Rosenbluth and M. N. Rosenbluth and A. H. Teller
- and E. Teller},
- title={Equation of State Calculations by Fast Computing Machines},
- journal={Journal of Chemical Physics},
- volume={21},
- year= 1953,
- pages={1087-1092}
-}
-
- at article{MicBloHil04,
- author={Charles Michalopoulos and Howard S. Bloom and Carolyn J. Hill},
- title={Can propensity-score methods match the findings from a random assignment
- evaluation of mandatory welfare-to-work programs?},
- journal={Review of Economics and Statistics},
- volume= 56,
- year= 2004,
- pages={156-179},
- number= 1
-}
-
- at article{Midlarsky05,
- author={Halbert White},
- title={A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct
- Test for Heteroskedasticity},
- abstract={This study seeks to distinguish between instances where genocide occurred
- and others where it might have been expected to occur but did not. Territorial
- loss, a corollary refugee influx, and a resulting contraction of socio-economic
- space are suggested to provide that distinction. Four analytic perspectives
- based on emotional reactions, class envy, prospect theory, and territoriality
- indicate the critical importance of loss. The theory is examined in the
- context of the mass murder of European Jewry including, of course, Germany
- and Austria, and all European German allies that allowed an indigenous
- genocidal impulse, willingness to comply with German genocidal policies,
- or an ability to resist German pressures for Jewish deportation. Three
- instances of perpetrating states - Italy, Vichy France, and Romania - emerge
- from the analysis. The latter two governments willingly collaborated with
- the Germans in victimizing their own Jewish citizenry, while Italy was
- on a genocidal path just prior to the German occupation. All five states
- mentioned above were found to experience considerable territorial loss
- and a contraction of socio-economic space. Bulgaria and Finland, on the
- other hand, actually expanded their borders at the start of the war and
- saved virtually all of their Jewish citizens. The importance of loss is
- demonstrated not only cross-sectionally, in the comparison between the
- five victimizers, on the one hand, and Bulgaria and Finland, on the other,
- but also diachronically, in the changing behavior over time of the genocidal
- and perpetrating states.},
- journal={Econometrica},
- volume={42},
- year={1980},
- pages={375-391},
- month={July},
- number={4},
- optnumber={4},
- optvolume={48},
- optpages={817--838},
- optmonth={May}
-}
-
- at article{Mierendorff30,
- author={Carl Mierendorff},
- title={Gesicht und Charakter der nationalsozialistischen Bewegung},
- journal={Gesellschaft},
- volume= 7,
- year= 1930,
- pages={489--540},
- number= 1
-}
-
- at article{MiiVuoOja97,
- author={Seppo Miilunpalo, Ilkka Vuori, Pekka Oja, Matti Pasanen, and Helka Urponen},
- title={Self Rated Health as a Health Measure: The Predictive Value of Self-Reported
- Health Status on the Use of Physician Services and on Mortality in the
- Working Age Population},
- journal={Journal of Clinical Epidemiology},
- volume= 50,
- year= 1997,
- pages={{517-28}}
-}
-
- at misc{MikSuc05,
- author={Gerome Miklau and Dan Suciu},
- title={Managing Integrity for Data Exchanged on the Web},
- year= 2005,
- month={16--17 June},
- howpublished={Eighth International Workshop on the Web and Databases, Baltimore},
- note={{http://webdb2005.uhasselt.be/papers/1-3.pdf}}
-}
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- at article{Miller01,
- author={Tim Miller},
- title={Increasing Longevity and Medicare Expenditures},
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- volume= 38,
- year= 2001,
- pages={215--226},
- month={May},
- number= 2
-}
-
- at inbook{MilReiHes98,
- author={Arthur H. Miller and William M. Reisinger and Vicki L. Hesli},
- title={Elections and Voters in Post-Communist Russia},
- chapter={Leader Popularity and Party Development in Post-Soviet Russia },
- year={100-135},
- publisher={London: Edward Elgar},
- editor={Matthew Wyman and Stephen White and Sarah Oates}
-}
-
- at article{MilRob89,
- author={Miller, Abraham H. and Robbins, James S.},
- title={Who Did Vote for Hitler? A Reanalysis of the Lipset/Bendix Controversy},
- journal={Polity},
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- year= 1989,
- pages={655-677},
- number= 4
-}
-
- at article{MilSha94,
- author={Paul Milgrom and Chris Shannon},
- title={Monotone Comparative Statics},
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- volume= 62,
- year= 1994,
- pages={157--180},
- month={January},
- number= 1,
- annote={introduction of the single crossing property as a way to ensure monotonicity}
-}
-
- at article{MinRos00,
- author={Ming, K. and Rosenbaum, Paul R.},
- title={Substantial gains in bias reduction from matching with a variable number
- of controls},
- journal={Biometrics},
- volume={56},
- year={2000},
- pages={118-124}
-}
-
- at article{MoeWal01,
- author={Karl Ove Moene and Michael Wallerstein},
- title={Inequality, Social Insurance, and Redistribution},
- journal={American Political Science Review},
- volume={95},
- year={2001},
- pages={859-874},
- month={December},
- number={4}
-}
-
- at article{MoeWal03,
- author={Karl Ove Moene and Michael Wallerstein},
- title={Earnings Inequality and Welfare Spending: A Disaggregated Analysis},
- journal={World Politics},
- volume={55},
- year={2003},
- pages={485-516},
- month={July}
-}
-
- at book{Mommsen89,
- author={Hans Mommsen},
- title={Die verspielte Freiheit --- der Weg der Republik von Weimar in den Untergang,
- 1918 bis 1933},
- publisher={Propyl{\"a}en},
- year= 1989
-}
-
- at techreport{MonLopGel99,
- author={Manuel Montes-y-Gomez and Aurelio Lopez-Loez and Alexander F. Gelbukh and
- Grigori Sidorov and Adolfo Guzman-Arenas},
- title={Text Mining: New Techniques and Applications},
- institution={Center for computing Research of the National Polytechnic Institute, Mexico
- City},
- year={1999},
- month={August},
- address={CIC, IPN, Laboratorio de Lenguaje Natural, Av. Juan de Dios Batiz, Mexico
- DF.},
- volume={34}
-}
-
- at techreport{MonLopGel99b,
- author={Manuel Montes y Gomez and Aurelio Lopez Lopez and Alexander F. Gelbukh},
- title={Text Mining as a Social Thermometer},
- institution={Centro de Investigaci{\'o}n en Computaci{\'o}n},
- year={1999},
- address={CIC, IPN Laboratorio de Lenguaje Natural. Ave. Juan de Dios Batiz, Mexico
- DF}
-}
-
- at book{MonSam04,
- title={Decentralization and Democracy in Latin America},
- publisher={University of Notre Dame Press},
- year={2004},
- editor={Alfred P. Montero and David J. Samuels},
- address={Notre Dame, Indiana}
-}
-
- at book{Montgomery2001,
- author={Douglas C. Montgomery},
- title={Design and Analysis of Experiments},
- publisher={Wiley},
- year={2001},
- address={New York},
- edition={5th}
-}
-
- at article{MorBlaTom03,
- author={Saul S. Morris and Robert E. Black and Lana Tomaskovic},
- title={Predicting the distribution of under-five deaths by cause in countries without
- adequate vital registration systems},
- journal={International Journal of Epidemiology},
- volume={32},
- year={2003},
- pages={1041-1051}
-}
-
- at book{Morozov84,
- author={V.A. Morozov},
- title={Methods for solving incorrectly posed problems},
- publisher={Springer-Verlag},
- year= 1984 ,
- address={Berlin}
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- at article{MorSpi99,
- author={Mary J. Morrissey and Donna Spiegelman},
- title={Matrix Methods for Estimating Odds Ratios with Misclassified Exposure Data:
- Extensions and Comparisons},
- journal={Biometrics},
- volume={55},
- year={1999},
- pages={338-344},
- month={June}
-}
-
- at unpublished{MorYamTat02,
- author={Satoshi Morinaga and Kenji Yamanishi and Kenji Tateishi and Toshikazu Fukushima},
- title={Mining Product Reputations on the Web},
- note={Satoshi Morinaga and Kenji Yamanishi NEC Corp. 4-1-1 Miyazaki Miyamae Kawasaki
- Kanagawa 216-8555 Japan Tel: 81-44-856-2143; morinaga at cw.jp.nec.com},
- year={2002}
-}
-
- at unpublished{MorYamTat02,
- author={Satoshi Morinaga and Kenji Yamanishi and Kenji Tateishi and Toshikazu Fukushima},
- title={Mining Product Reputations on the Web},
- note={Satoshi Morinaga and Kenji Yamanishi NEC Corp. 4-1-1 Miyazaki Miyamae Kawasaki
- Kanagawa 216-8555 Japan Tel: 81-44-856-2143; morinaga at cw.jp.nec.com},
- year={2002}
-}
-
- at article{MosSha82,
- author={Jana Mossey MPH, PhD, and Evelyn SHapira, MA},
- title={Self-Rated Health: A Predictor of Mortality Among the Elderly},
- journal={American Journal of Public Health},
- volume= 72,
- year= 1982,
- pages={{800-08}}
-}
-
- at article{moynihan00,
- author={Ray Moynihan and Lisa Bero and Dennis Ross-Degnan and David Henry and Kriby
- Lee and Judy Watkins and Connie Mah and Stephen B. Soumerai},
- title={Coverage by the News Media of the Benefits and Risks of Medications},
- journal={New England Journal of Medicine},
- volume= 342,
- year= 2000,
- pages={1645-1650},
- month={June 1},
- number= 22
-}
-
- at article{MugLac02,
- author={Anthony Mughan and Dean Lacy},
- title={Economic Performance, Job Insecurity, and Electoral Choice},
- journal={British Journal of Political Science},
- volume= 32,
- year= 2002,
- pages={513--533}
-}
-
- at book{MurEva03,
- title={Health Systems Performance Assessment: Debates, Methods and Empiricism},
- publisher={World Health Organization},
- year= 2003,
- editor={Christopher J.L. Murray and David B. Evans},
- address={Geneva}
-}
-
- at book{MurLop96,
- title={The Global Burden of Disease},
- publisher={Harvard University Press and WHO},
- year= 1996 ,
- editor={Christopher L.J.\ Murray and Alan D.\ Lopez}
-}
-
- at article{MurLop97,
- author={Christopher J. L. Murray and Alan D. Lopez},
- title={Mortality by Cause for Eight Regions of the World: Global Burden of Disease
- Study},
- journal={The Lancet},
- volume={349},
- year={1997},
- pages={1269-1276}
-}
-
- at article{murphy69,
- author={George G. S. Murphy},
- title={On Counterfactual Propositions},
- journal={History and Theory},
- volume= 9,
- year= 1969,
- pages={14-38}
-}
-
- at book{Murphy72,
- author={Paul L. Murphy},
- title={The Meaning of Freedom of Speech},
- publisher={Greenwood},
- year= 1972,
- address={Westport, CT}
-}
-
- at book{Murray98,
- author={Murray, David M.},
- title={Design and Analysis of Group-Randomized Trials},
- publisher={Oxford UP},
- year={1998},
- address={New York}
-}
-
- at book{Mutz98,
- author={Diana C. Mutz},
- title={Impersonal Influence: How Perceptions of Mass Collectives Affect Political
- Attitudes},
- publisher={Cambridge University Press},
- year={1998},
- address={New York, NY}
-}
-
- at article{MwaLesDec05,
- author={Samuel M. Mwalili and Emmanuel Lesaffre and Dominique Declerck},
- title={A Bayesian ordinal logistic regression model to correct for interobserver
- measurement error in a geographical oral health study},
- journal={Applied Statistics},
- volume={54},
- year={2005},
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-}
-
- at article{Myerson04,
- author = {Roger Myerson},
- year = {2004},
- title = {Political Economics and the Weimar Disaster},
- journal = {Journal of Institutional and Theoretical Economics},
- pages = {187-209},
- volume = {160}
-}
-
- at article{Nagler91,
- author={Jonathan Nagler},
- title={{The Effect of Registration Laws and Education on U. S. Voter Turnout}},
- journal= apsr,
- volume={85},
- year={1991},
- pages={1393--1405},
- number={4}
-}
-
- at unpublished{NasYi03,
- author={Tetsuya Nasukawa and Jeonghee Yi},
- title={Sentiment Analysis: Capturing Favoriability Using Natural Language Processing},
- note={Tetsuya Nasukawa IBM Research, Tokyo Research Laboratory 1623-14 Shimotsuruma,
- Yamato-shi, Kanagawa-ken, 242-8502, Japan; nasukawa at jp.ibm.cop},
- year={2003},
- month={October}
-}
-
- at unpublished{NasYi03,
- author={Tetsuya Nasukawa and Jeonghee Yi},
- title={Sentiment Analysis: Capturing Favoriability Using Natural Language Processing},
- note={Tetsuya Nasukawa IBM Research, Tokyo Research Laboratory 1623-14 Shimotsuruma,
- Yamato-shi, Kanagawa-ken, 242-8502, Japan; nasukawa at jp.ibm.cop},
- year={2003},
- month={October}
-}
-
- at book{National02,
- author={NIPSSR},
- title={Population Projections for Japan (January, 2002)},
- publisher={National Institute of Population and Social Security Research},
- year= 2002,
- annote={Life tables for Japan are constructed using the Lee-Carter method.}
-}
-
- at book{Neuendorf02,
- author={Neuendorf, K.A.},
- title={{The Content Analysis Guidebook}},
- publisher={Thousand Oaks, CA: Sage Publications},
- year={2002}
-}
-
- at article{Neuhaus02,
- author={John M. Neuhaus},
- title={Analysis of Clustered and Longitudinal Binary Data Subject to Response Misclassification},
- journal={Biometrics},
- volume={58},
- year={2002},
- pages={675-683},
- month={September}
-}
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- at article{Neuhaus99,
- author={John M. Neuhaus},
- title={Bias and efficiency loss due to misclassified responses in binary regression},
- journal={Biomtrika},
- volume={86},
- year={1999},
- pages={843-855},
- number={4}
-}
-
- at article{neutra78,
- author={Raymond R. Neutra and Margaret E. Drolette},
- title={Estimating Exposure-Specific Disease Rates from Case-Control Studies Using
- Bayes Theorem},
- journal={American Journal of Epidemiology},
- volume= 108,
- year= 1978,
- pages={214-222},
- number= 3
-}
-
- at article{Neyman23,
- author={J. Neyman},
- title={On the application of probability theory to agricultural experiments. Essay
- on Principles. Section 9},
- journal={Statistical Science},
- volume={5},
- year={1923},
- pages={465-480},
- note={Translated in 1990, with discussion}
-}
-
- at article{Neyman23b,
- author={J. Neyman},
- title={Statistical Problems in Agricultural Experiments},
- journal={Journal of the Royal Statistical Association},
- volume= 2,
- year= 1923,
- pages={107--180},
- number= 2
-}
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- at article{Nickerson05,
- author={David W. Nickerson},
- title={Scalable Protocols Offer Efficient Design for Field Experiements},
- journal={Political Analysis},
- volume={13},
- year={2005},
- pages={233-252}
-}
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- at article{NieFet86,
- author={Richard G. Niemi and Patrick Fett},
- title={The Swing Ratio: An Explanation and an Assessment},
- journal={Legislative Studies Quarterly},
- volume={11},
- year={1986},
- pages={75-90},
- month={February},
- number={1}
-}
-
- at misc{NISO01,
- author={NISO},
- title={The Dublin Core Metadata Element Set},
- year={2001},
- note={{http://www.niso.org/standards/resources/Z39-85.pdf}}
-}
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- at article{NiyGirPog98,
- author = {P. Niyogi and F. Girosi and T. Poggio},
- title = {Incorporating Prior Information in Machine Learning
- by Creating Virtual061 Examples},
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- volume = {86},
- year = {1998},
- pages = {2196--2209},
- number = {11}
-}
-
- at book{Noakes71,
- author={Noakes, J.},
- title={The Nazi Party in Lower Saxony},
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- year= 1971,
- address={New York}
-}
-
- at article{NovReaRau06,
- author={Scott P. Novak and Sean F. Reardon and Stephen W. Raudenbush and Stephen
- L. Buka},
- title={Retail tobacco outlet density and youth cigarette smoking: A propensity-modeling
- approach},
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- volume={96},
- year={2006},
- pages={670-676},
- month={April},
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- at article{nurminen95,
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- year= 1995,
- number={365-371}
-}
-
- at article{NybPetGai03,
- author={Hanne Nybo et al},
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- year= 2003,
- pages={{1365-73}}
-}
-
- at booklet{OetParHym03,
- title={The Not So Short Introduction to \LaTeXe\}, author = {Tobias Oetiker, Hubert
- Partl, Irene Hyma and Elisabeth Schlegl}, year = 2003, note = {{Available
- at http://www.ctan.org/tex-archive/info/lshort/english/lshort.pdf.}}
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- at article{OhaWooMoo90,
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- title={Practical Bayesian Analysis of a Simple Logistic Regression: Predicting
- Corneal Transplants},
- journal={Statistics in Medicine},
- volume={9},
- year={1990},
- pages={1091-1101}
-}
-
- at book{Ohr97a,
- author = {Dieter Ohr},
- title = {Nationalsozialistische Propaganda und Weimarer
- Wahlen: empirische Analysen zur Wirkung von
- NSDAP-Versammlungen},
- publisher = {Westdeutscher Verlag},
- year = 1997,
- address = {Opladen}
-}
-
- at article{Ohr97b,
- author={Dieter Ohr},
- title={Nationalsozialistische Versammlungspropaganda und Wahlerfolg der NSDAP:
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- volume= 22,
- year= 1997,
- pages={106--127},
- number={3/4}
-}
-
- at article{OkoDev01,
- author={Ike S. Okosun and G.E. Alan Dever},
- title={Verbal Autopsy: A Necessary Solution for the Paucity of Mortality Data in
- the Less-Developed Countries},
- journal={Ethnicity and Disease},
- volume={11},
- year={2001},
- pages={575-577}
-}
-
- at article{OkoDev01,
- author={Ike S. Okosun and G.E. Alan Dever},
- title={Verbal Autopsy: A Necessary Solution for the Paucity of Mortality Data in
- the Less-Developed Countries},
- journal={Ethnicity and Disease},
- volume={11},
- year={2001},
- pages={575-577}
-}
-
- at article{OloFliAns94,
- author={John O'Loughlin and Colin Flint and Luc Anselin},
- title={The Geography of the Nazi Vote: Context, Confession, and Class in the Reichstag
- Election of 1930},
- journal={Annals of the Association of American Geographers},
- volume= 84,
- year= 1994,
- pages={351-380}
-}
-
- at article{O'Loughlin02,
- author={John O'Loughlin},
- title={The Electoral Geography of Weimar Germany},
- journal={Political Analysis},
- volume= 10,
- year= 2002,
- pages={217--243},
- number= 3
-}
-
- at article{Oman85,
- author={Samuel D. Oman},
- title={Specifying a Prior Distribution in Structured Regression Problems},
- journal= jasa,
- volume= 80,
- year= 1985,
- pages={190--195},
- month={March},
- number= 389
-}
-
- at article{OneRus97,
- author={John R. Oneal and Bruce Russett},
- title={The Classical Liberals Were Right: Democracy, Interdependence, and Conflict,
- 1950-1985},
- journal= isq,
- volume= 41,
- year= 1997,
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- 84112; riloff at cs.utah.edu}
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- Effects},
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- volume= 45,
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-}
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- author = {Paul R. Rosenbaum and Donald B. Rubin},
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- author={Rosenbaum, P.R. and Rubin, D.B.},
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- author={Alexander K Rowe},
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- title={A Method to Increase the Power of Multiple Testing Procedures Through Sample
- Splitting},
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- volume={5},
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- author={Donald B. Rubin},
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- to the tobacco litigation},
- journal={Heatlh Services \& Outcomes Research Methodology},
- volume={2},
- year={2001},
- pages={169-188},
- month={December},
- number={3-4}
-}
-
- at unpublished{Rubin04,
- author={Donald B. Rubin},
- title={Discussion of ``{P}rinciples for modeling propensity scores in medical research:
- a systematic literature review"},
- note={Forthcoming in {\it Pharmacoepidemiology and Drug Safety}. Referenced paper
- by Weitzen, Lapane, Toledano, Hume, Mor},
- year= 2004
-}
-
- at book{Rubin06,
- author={Donald B. Rubin},
- title={Matched Sampling for Causal Effects},
- publisher={Cambridge University Press},
- year= 2006 ,
- address={Cambridge, England}
-}
-
- at article{Rubin80,
- author={Rubin, Donald B.},
- title={Comments on ``Randomization Analysis of Experimental Data: The Fisher Randomization Test'', by D. Basu},
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- volume={75},
- year={1980},
- pages={591-593}
-}
-
-
-
- at article{Rubin73,
- author={Rubin, Donald B.},
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- volume={29},
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-}
-
- at article{Rubin73b,
- author={Rubin, Donald B.},
- title={The use of matched sampling and regression adjustment to remove bias in
- observational studies},
- journal={Biometrics},
- volume={29},
- year={1973},
- pages={185-203}
-}
-
- at article{rubin74,
- author={Donald B. Rubin},
- title={Estimating Causal Effects of Treatments in Randomized and Nonrandomized
- Studies},
- journal={Journal of Educational Psychology},
- volume= 6,
- year= 1974,
- pages={688--701}
-}
-
- at article{Rubin76,
- author={Donald Rubin},
- title={Inference and Missing Data},
- journal={Biometrika},
- volume={63},
- year={1976},
- pages={581-592}
-}
-
- at article{Rubin77,
- author={Donald Rubin},
- title={Formalizing Subjective Notions about the Effect of Nonrespondents in Sample
- Surveys},
- journal={Journal of the American Statistical Association},
- volume={72},
- year={1977},
- pages={538-543},
- month={September},
- number={359}
-}
-
- at article{Rubin77b,
- author={Donald B. Rubin},
- title={Assignment to Treatment Group on the Basis of a Covariate},
- journal={Journal of Educational Statistics},
- volume={2},
- year={1977},
- pages={1},
- number={1-26}
-}
-
- at article{Rubin78,
- author={Donald B. Rubin},
- title={Bayesian inference for causal effects: The role of randomization},
- journal={The Annals of Statistics},
- volume={6},
- year={1978},
- pages={34-58}
-}
-
- at article{Rubin79,
- author={Donald B. Rubin},
- title={Using Multivariate Matched Sampling and Regression Adjustment to Control
- Bias in Observational Studies},
- journal= jasa,
- volume={74},
- year={1979},
- pages={318--328}
-}
-
- at book{Rubin87,
- author={Donald B. Rubin},
- title={Multiple Imputation for Nonresponse in Surveys},
- publisher={John Wiley},
- year={1987},
- address={New York}
-}
-
- at article{Rubin87b,
- author={Donald Rubin},
- title={A Noniterative sampling/importance resampling alternative to the data augmentation
- algorithm for creating a few imputations when fractions of missing information
- are modest: the SIR Algorithm, Discussion of Tanner and Wong},
- journal={Journal of the American Statistical Assocaition},
- volume={82},
- year={1987},
- pages={543-546}
-}
-
- at article{Rubin91,
- author={Donald B. Rubin},
- title={Practical implications of modes of statistical inference for causal effects
- and the critical role of the assignment mechanism},
- journal={Biometrics},
- volume= 47,
- year= 1991,
- pages={1213-1234}
-}
-
- at article{Rubin94,
- author={Donald B. Rubin},
- title={Missing Data, Imputation, and the Bootstrap: Comment},
- journal={Journal of the American Statistical Association},
- volume={89},
- year={1994},
- pages={475-478},
- month={Jun},
- number={426}
-}
-
- at article{Rubin96,
- author={Donald B. Rubin},
- title={Multiple Imputation after 18+ Years},
- journal= jasa,
- volume= 91,
- year= 1996,
- pages={473--489},
- number= 434
-}
-
- at article{Rubin96,
- author={Donald Rubin},
- title={Multiple Imputation after 18+ Years},
- journal={Journal of the American Statistical Association},
- volume={91},
- year={1996},
- pages={473-489}
-}
-
- at article{Rubin97,
- author={Donald B. Rubin},
- title={Estimating causal effects from large data sets using propensity scores},
- journal={Annals of Internal Medicine},
- volume= 127,
- year= 1997,
- pages={757-763}
-}
-
- at article{RubSch86,
- author={Donald Rubin and Nathaniel Schenker},
- title={Multiple Imputation for Interval Estimation for Simple Random Samples with
- Ignorable Nonresponse},
- journal= jasa,
- volume= 81,
- year= 1986,
- pages={366-374},
- number= 394
-}
-
- at article{RubSch87,
- author={Donald B. Rubin and Nathaniel Schenker},
- title={Logit-Based Interval Estimation from Binomial Data Using the Jeffreys Prior},
- journal={Sociological Methodology},
- volume={17},
- year={1987},
- pages={131-144}
-}
-
- at inproceedings{RubSch90,
- author={D.B. Rubin and J.L. Schafer},
- title={Efficiently Creating Multiple Imputations for Incomplete Multivariate Normal
- Data},
- booktitle={Proceedings of the Statistical Computing Section of the American Statistical
- Association},
- year={1990},
- pages={83-88}
-}
-
- at article{RubStu06,
- author={Donald B. Rubin and Elizabeth A. Stuart},
- title={Affinely invariant matching methods with discriminant mixtures of proportional
- ellipsoidally symmetric distributions},
- journal={Annals of Statistics},
- volume= 34,
- year={2006},
- pages={1814-1826},
- number= 4
-}
-
- at article{RubTho00,
- author={Donald B. Rubin and Neal Thomas},
- title={Combining propensity score matching with additional adjustments for prognostic
- covariates},
- journal={Journal of the American Statistical Association},
- volume= 95,
- year={2000},
- pages={573-585}
-}
-
- at article{RubTh,
- author={Donald B. Rubin and Neal Thomas},
- title={Characterizing the Effect of Matching Using Linear Propensity Score Methods
- With Normal Distributions},
- journal={Biometrika},
- volume={79},
- year={1992},
- pages={797-809}
-}
-
- at article{RubTho96,
- author={Donald B. Rubin and Neal Thomas},
- title={Matching Using Estimated Propensity Scores, Relating Theory to Practice},
- journal={Biometrics},
- volume={52},
- year={1996},
- pages={249-264}
-}
-
- at unpublished{RugKimMar03,
- author = {Theodore W. Ruger and Pauline T. Kim and Andrew
- D. Martin and Kevin M. Quinn},
- title = {The Supreme Court Forecasting Project: Legal and
- Political Science Approaches to Predicting Supreme
- Court Decision-Making},
- note = {Washington University in St. Louis},
- year = 2003
-}
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- year= 1988,
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- title={Effect of Clopidogrel Pretreatment Before Percutaneous Coronary Intervention
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- Louise Burton and Ann McClintock and Robert Carter and Allan Donner and
- Sylvan Green },
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- author = {Voth, Hans-Joachim},
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- Errors in Regression}},
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- year= 1978,
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-}
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- at incollection{Wahba79,
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- month={January 8--10},
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-}
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- at incollection{Wahba80a,
- author={G. Wahba},
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- approximation problems with large quantities of noisy data},
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- address={New York},
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-}
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- the generalized splines smoothing problem},
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-}
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- at book{Wahba90,
- author={G. Wahba},
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- year= 1990 ,
- address={Philadelphia}
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- at techreport{WahLinZha99,
- author={G. Wahba and Y. Lin and H. Zhang},
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- of Washington}
-}
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- author={Jeremy Waldron},
- title={Law and disagreement},
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- address={New York}
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- author={L.A. Waller and B.P. Carlin and H. Xia and A.E. Gelfand},
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- volume= 92,
- year= 1997,
- pages={607--617},
- number= 438
-}
-
- at techreport{WalHogHam06,
- author={Robert Walker and Lesley Hoggart and Gayle Hamilton with Susan Blank},
- title={Making random assignment happen: Evidence from the UK Employment Retention
- and Advancement (ERA) demonstration},
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- year={2006},
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- Medications},
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- month={December}
-}
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- at article{WanSha91,
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- year= 1991,
- pages={{239-45}},
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-}
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- at unpublished{WanYanMa06,
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- verbal autopsies},
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-}
-
- at book{WapBerBra40,
- author={Waples, D. and Berelson, B. and Bradshaw, F.R.},
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- of Reading and a Statement of Problems for Research}},
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- year={1940}
-}
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- at article{Ware05,
- author={Helen Ware},
- title={Demography, Migration and Conflict in the Pacific},
- abstract={This article explores the relationships between demography and internal
- conflict in the Pacific Island countries, focusing on the three subregions
- Polynesia, Micronesia and Melanesia. These countries confront distinctive
- challenges and opportunities because of their unique cultures and non-militarized
- status, combined with very small size and remote locations. The use of
- the MIRAB model of island economies based on migration, remittances, aid
- and bureaucracy is extended to examine its impact on social cohesion and
- the avoidance of internal conflict. For Polynesia, MIRAB is found to be
- a sustainable development strategy. Continuous emigration from Polynesia
- serves to reduce population pressure and communal tensions. Further, remittance
- income supports the Polynesian economies, and this also reduces the potential
- for conflict. For Micronesia, except Kiribati and Nauru, migration access
- to the USA is assured. In contrast, for the Melanesian countries, there
- is minimal emigration, rapid population growth and considerable intercommunal
- tension, which has resulted in several coups and one 'failed state'. Demographic
- pressure created by rapid population growth results in a lack of employment
- opportunities for youths (who provide the majority of participators in
- civil unrest and conflicts) rather than in direct pressure on land and
- other natural resources.},
- journal={Journal for Peace Research},
- volume={42},
- year={2005},
- pages={435-454},
- month={July},
- number={4}
-}
-
- at unpublished{WarSivCao05,
- author={Michael D. Ward and Randolph M. Siverson and Xun Cao},
- title={Everybody Out of the Pool!},
- note={Michael Ward, Dept of Politcal Science, Univ of WA, Seattle mdw at u.washington.edu},
- year={2005},
- month={August}
-}
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- at techreport{WasRoe06,
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- title={Weighted Hypothesis Testing},
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- month={April}
-}
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- year={1994},
- pages={233-287},
- number={2}
-}
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- at article{Weibe04,
- author={Janyce M. Wiebe},
- title={Tracking Point of View in Narrative},
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- volume={20},
- year={1994},
- pages={233-287},
- number={2}
-}
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- Heart Disease Policy Model},
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- year= 1987,
- pages={1417--1426},
- number= 11
-}
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- author={Noel S. Weiss},
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- volume={Volume 11},
- address={New York},
- series={Monographs in Epidemiology and Biostatistics }
-}
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- author={Greg C. Wei and Martin A. Tanner},
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- Augmentation Algorithms},
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- volume={85},
- year={1990},
- pages={699-704},
- month={September}
-}
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- Bayes Factors},
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-}
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- Rational Choice in Italy}},
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- number = {01},
- pages = {91--106},
- year = {2003}
-}
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- month={June}
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-}
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- address={New York}
-}
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- at article{WesHarMig85,
- author={Mike West and P. Jeff Harrison and Helio S. Migon},
- title={Dynamic Generalized Linear Models and Bayesian Forecasting},
- journal={Journal of the American Statistical Association},
- volume={80},
- year={1985},
- pages={73-83},
- month={March},
- number={389}
-}
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- at article{Western95,
- author={Bruce Western},
- title={{Concepts and Suggestions for Robust Regression Analysis}},
- journal={American Journal of Political Science},
- volume={39},
- year={1995},
- pages={786--817},
- number={3}
-}
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- at article{Western98,
- author={Bruce Western},
- title={{Causal Heterogeneity in Comparative Research: a Bayesian Hierarchical Modelling
- Approach}},
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- volume= 42,
- year= 1998,
- pages={1233--1259},
- month={October},
- number= 4
-}
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- at article{WhiEva96,
- author={Stephen Whitefield and Geoffrey Evans},
- title={Support for Democracy and Poltical Opposition in Russia 1993-95},
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- volume={12},
- year={1996},
- pages={218-52},
- number={3}
-}
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- at book{WhiRosMcA97,
- author={Stephen White and Richard Rose and Ian McAllister},
- title={How Russia Votes},
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- address={Chatham, NJ}
-}
-
- at unpublished{WhiSetCha06,
- author={David R. Whiting and Philip W. Setel and Daniel Chandramohan and Lara J.
- Wolfson and Yusuf Hemed and Alan D. Lopez},
- title={Estimating Cause-Specific Mortality from Community- and Facility-Based Data
- Sources in Tanzania: Options and Implications for Mortality Burden Estimates},
- note={Whiting, MEASURE Evaluation, Carolina Population Center, Univ. of NC at
- Chapel Hill, Dept of Medicine, School of Clinical Medical Sciences, Univ
- of Newcastle upon Tyne England; david.whiting at ncl.ac.uk},
- year={2006}
-}
-
- at article{Whitbeck05,
- author={Caroline Whitbeck},
- title={The Responsible Collection, Retention, Sharing, and Interpretation of Data},
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- year= 2005,
- note={{http://onlineethics.org/reseth/mod/data.html}}
-}
-
- at article{White02,
- author={Kevin M. White},
- title={Longevity Advances in High-IncomeCountries, 1955-96},
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- volume= 28,
- year= 2002,
- pages={59--76},
- month={March},
- number= 1
-}
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- at article{White80,
- author={Halbert White},
- title={A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct
- Test for Heteroskedasticity},
- journal={Econometrica},
- volume={48},
- year={1980},
- pages={817--838},
- month={May},
- number={4}
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- at book{White82,
- author={Halbert L. White},
- title={Asymptotic Theory For Econometricians},
- publisher={Academic Press},
- year= 1984,
- address={New York}
-}
-
- at book{White92,
- author={Halbert H. White},
- title={Artificial Neural Networks, Approximation and Learning Theory},
- publisher={Blackwell},
- year= 1992,
- address={Cambridge, MA}
-}
-
- at article{Whittaker23,
- author={{Whittaker E.T.}},
- title={On a New Method of Graduation},
- journal={Proceedings of the Edinburgh Mathematical Society},
- volume= 41,
- year= 1923,
- pages={63--75}
-}
-
- at article{WidKub96,
- author={Widmer, G. and Kubat, M.},
- title={{Learning in the presence of concept drift and hidden contexts}},
- journal={Machine Learning},
- volume={23},
- year={1996},
- pages={69--101},
- number={1},
- publisher={Springer}
-}
-
- at unpublished{WieWilBel01,
- author={Janyce Wiebe and Theresa Wilson and Matthew Bell},
- title={Identifying Collocations for Recognizing Opinions},
- note={University of Pittsburgh wiebe, twilson, mbell at cs.pitt.edu},
- year={2001},
- month={April}
-}
-
- at article{WilBerNob01,
- author={B.P. Will and J.M. Berthelot and K.M. Nobrega and W. Flanagan and W.K. Evans},
- title={Canada's Population Health Model (POHEM): A Tool for Performing Economic
- Evaluations of Cancer Control Interventions},
- journal={European Journal of Cancer},
- volume= 37,
- year= 2001,
- pages={1797--1804}
-}
-
- at article{WilGouBos02,
- author={Brian G. Williams and Eleanor Gouws and Cynthia Boschi-Pinto and Jennifer
- Bryce and Christopher Dye},
- title={Estimates of world-wide distribution of child deaths from acute respiratory
- infections},
- journal={The Lancet Infectious Diseases},
- volume={2},
- year={2002},
- pages={25-32},
- month={January}
-}
-
- at article{WilGouBos02,
- author={Brian G. Williams and Eleanor Gouws and Cynthia Boschi-Pinto and Jennifer
- Bryce and Christopher Dye},
- title={Estimates of world-wide distribution of child deaths from acute respiratory
- infections},
- journal={The Lancet Infectious Diseases},
- volume={2},
- year={2002},
- pages={25-32},
- month={January}
-}
-
- at article{WilHol07,
- author={Elizabeth Ty Wilde and Robinson Hollister},
- title={How Close is Close Enough? Evaluating Propensity Score Matching Using Data
- from a Class-Size Reduction Experiment},
- journal={Journal of Policy Analysis and Management},
- volume={26},
- year={2007},
- number={3}
-}
-
- at techreport{Wilmoth93,
- author={John Wilmoth},
- title={{Computational Methods for Fitting and Extrapolating the Lee-Carter Model
- of Mortality Change}},
- institution={Department of Demography, University of California, Berkeley},
- year= 1993
-}
-
- at incollection{Wilmoth96,
- author={John R. Wilmoth},
- title={Mortality Projections for Japan: A Comparison of Four Methods},
- booktitle={Health and Mortality Among Elderly Populations},
- publisher={Oxford University Press},
- year= 1996,
- address={Oxford},
- editor={G. Caselli and Alan Lopez},
- pages={266-287}
-}
-
- at article{Wilmoth98,
- author={John Wilmoth},
- title={The Future of Human Longevity: A Demographer's Perspective},
- journal={Science},
- volume= 280,
- year= 1998,
- pages={395--397},
- month={April 17},
- number= 5362
-}
-
- at article{Wilmoth98b,
- author={John Wilmoth},
- title={Is the Pace of Japanese Mortality Decline Converging Towards International
- Trends?},
- journal={Population and Development Review},
- volume= 24,
- year= 1998,
- pages={593--600},
- number= 3
-}
-
- at article{WinMar92,
- author={Christopher Winship and Robert D. Mare},
- title={Models for Sample Selection Bias},
- journal={Annual Review of Sociology},
- volume={18},
- year={1992},
- pages={327-50}
-}
-
- at article{WinMor99,
- author={Christopher Winship and Stephen L. Morgan},
- title={The Estimation of causal Effects from Observational Data},
- journal={American Review of Sociology},
- volume= 25,
- year= 1999,
- pages={659--707}
-}
-
- at article{WinRad94,
- author={Christopher Winship and Larry Radbill},
- title={Sampling Weights and Regression Analysis},
- journal={Sociological Methods and Research},
- volume={23},
- year={1994},
- pages={230-257},
- month={November},
- number={2}
-}
-
- at unpublished{WinSob00,
- author={Christopher Winship and Michael Sobel},
- title={Causal Inference in Sociological Studies},
- note={Harvard University},
- year= 2000
-}
-
- at article{WirLin94,
- author={D.N. Wirawan and M. Linnan},
- title={The Bali indirect maternal mortality study},
- journal={Studies in Family Planning},
- volume= 5,
- year= 1994,
- pages={304--309}
-}
-
- at inbook{WolCalJoh94,
- author = {F.D. Wolinsky, C.M. Callahan, and R.J. Johnson},
- title = {Subjective Health Status and Mortality in the
- Elderly},
- year = 1994,
- publisher = {{New York: Springer Publishing Company}},
- pages = {{13-28}},
- journal = {Facts and Research in Gerontology}
-}
-
- at article{WolFir02,
- author = {Rory Wolfe and David Firth},
- title = {Modelling Subjective Use of an Ordinal Reponse Scale
- in a Many Period Crossover Experiment},
- journal = {Applied Statistics},
- volume = 51,
- year = 2002,
- pages = {245--255},
- month = {April},
- number = 2
-}
-
- at article{WolJoh92,
- author = {Fredric Wolinsky and Robert Johnson},
- title = {Perceived Health Status and Mortality Among Older
- Men and Women},
- journal = {Journal of Gerontology: Social Sciences},
- volume = 47,
- year = 1992,
- pages = {{S304-12}}
-}
-
- at article{WolJohStu95,
- author = {Fredric D. Wolinsky, Robert L. Johnson, and Timothy
- E. Stump},
- title = {The Riske of Mortality among Older Adults over an
- Eight-Year Period},
- journal = {The Gerontologist},
- volume = 35,
- year = 1995,
- pages = {{150-61}}
-}
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- at article{WonBenKof98,
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- at misc{Leisch99,
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- Trust Funds}},
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- editor = {Crimmins, Eileen and Preston, Samuel and Cohen, Barney},
- title = {Explaining Divergent Levels of Longevity in High-Income Countries},
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-}
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- at Article{PSC09,
- author = {{Prospective Studies Collaboration}},
- title = {Body-mass index andc cause-specific mortality in 900 000 adults: collaborative analyses of 57 prospective studies},
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-}
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- at Article{BauPeaPri06,
- author = {Baur, Joseph and Pearson, Kevin and Price, Nathan and Jamieson, Hamish and Lerin, Carles and Kalra, Avash and Prabhu, Vinayakumar and Allard, Joanne and Lopez-Lluch, Guillermo and Lewis, Kaitlyn and Pistell, Paul and Poosala, Suresh and Becker, Kevin and Boss, Olivier and Gwinn, Dana and Wang, Mingyi and Ramaswamy, Sharah and Fishbein, Kenneth and Spencer, Richard and Lakatta, Edward and Le Couteur, David and Shaw, Reuben and Navas, Placido and Puigserver, Pere and Ingram, [...]
- title = {Resveratrol improves health and survival of mice on a high-calorie diet},
- journal = {Nature},
- year = 2006,
- volume = 444,
- number = 16,
- pages = {337-342}
-}
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- @Unpublished{PreSto10,
- author = {Preston, Samuel and Stokes, Andrew},
- title = {Is the high level of obesity in the United States related to its low life expectancy?},
- note = {Working Paper 2010-08, Population Studies Center, University of Pennsylvania},
- year = {2010}
- }
-
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- at Article{FleCarOgd10,
- author = {Flegal, Katherine and Carroll, Margaret and Ogden, Cynthia and Curtin, Lester},
- title = {Prevalence and trends in obesity among US adults, 1999-2008},
- journal = {The Journal of the American Medical Assocation},
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- volume = 303,
- number = 3,
- pages = {235-241}
-}
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- at Article{BerKimCat06,
- author = {Bergman, Richard and Kim, Stella and Catalano, Karyn and Hsu, Isabel and Chiu, Jenny and Kabir, Morvarid and Hucking, Katrin and Ader, Marilyn},
- title = {Why visceral fat is bad: mechanisms of the metabolic syndrome},
- journal = {Obesity},
- year = 2006,
- volume = 14,
- number = {Supplement 1},
- pages = {16S-19S}
-}
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- at Article{SniVanVis06,
- author = {Snijder,M.B. and {van Dam},R.M. and Visser,M. and Seidell,J.C.},
- title = {What aspects of body fat are particularly hazardous and how do we measure them?},
- journal = {International Journal of Epidemiology},
- year = 2006,
- volume = 35,
- number = 1,
- pages = {83-92}
-}
-
- at Article{EzzMarSkj06,
- author = {Ezzati, Majid and Martin, Hilarie and Skjold, Suzanne and Vander Hoorn, Stephen and Murray, Christopher},
- title = {Trends in national and state-level obesity in the USA after correction for self-report bias: analysis of health surveys},
- journal = {Journal of the Royal Society of Medicine},
- year = 2006,
- volume = 99,
- number = 5,
- pages = {250-257}
-}
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- at Article{EzzFriKul08,
- author = {Ezzati, M. and Friedman, Ari B. and Kulkarni, Sandeep and Murray, Christopher},
- title = {The reversal of fortunes: Trends in county mortality and cross-county mortality disparities in the United States},
- journal = {PLoS Medicine},
- year = 2008,
- volume = 5,
- number = 4,
- note = {e66},
- pages = {0557-0568}
-}
-
- at Article{TorVau11,
- author = {Torri, T. and Vaupel, J.W.},
- title = {Forecasting life expectancy in an international context},
- journal = {International Journal of Forecasting},
- year = 2011,
- volume = 27,
- note = {Forthcoming}
-}
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- at Article{LiLee05,
- author = {Li, Nan and Lee, Ronald},
- title = {Coherent mortality forecasts for a group of populations: an extension of the Lee-Carter method},
- journal = {Demography},
- year = 2005,
- volume = 42,
- number = 3,
- pages = {575-594}
-}
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- at Article{HugKeeNau04,
- author = {Hughes, JR and Keely, J and Naud, S.},
- title = {Shape of the relapse curve and long-term abstinence among untreated smokers},
- journal = {Addiction},
- year = 2004,
- volume = 99,
- number = 1,
- pages = {29-38}
-}
-
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- at article{SuhAtzCho08,
-author = {Suh, Yousin and Atzmon, Gil and Cho, Mi-Ook and Hwang, David and Liu, Bingrong and Leahy, Daniel J. and Barzilai, Nir and Cohen, Pinchas},
-title = {Functionally significant insulin-like growth factor I receptor mutations in centenarians},
-volume = {105},
-number = {9},
-pages = {3438-3442},
-year = {2008},
-journal = {Proceedings of the National Academy of Sciences}
-}
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- at article{MaiGoyPle03,
-author = {Mair, William and Goymer, Patrick and Pletcher, Scott D. and Partridge, Linda},
-title = {Demography of Dietary Restriction and Death in Drosophila},
-volume = {301},
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-pages = {1731-1733},
-year = {2003},
-journal = {Science}
-}
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-author = {Masuzaki, Hiroaki and Paterson, Janice and Shinyama, Hiroshi and Morton, Nicholas M. and Mullins, John J. and Seckl, Jonathan R. and Flier, Jeffrey S.},
-title = {A Transgenic Model of Visceral Obesity and the Metabolic Syndrome},
-volume = {294},
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-pages = {2166-2170},
-year = {2001},
-journal = {Science}
-}
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- author = {Kenyon, Cynthia and Chang, Jean and Gensch, Erin and Rudner, Adam and Tabtiang, Ramon},
- title = {A C. elegans mutant that lives twice as long as wild type},
- journal = {Nature},
- year = 1993,
- volume = 366,
- pages = {461-464}
-}
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- at Article{KojKamAiz04,
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- title = {Association analysis between longevity in the Japanese population and polymorphic variants of genes involved in insulin and insulin-like growth factor 1 signaling pathways},
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- year = 2004,
- volume = 39,
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- pages = {1595 - 1598}
-}
diff --git a/vignettes/gkpubs.bib b/vignettes/gkpubs.bib
deleted file mode 100644
index e9b910d..0000000
--- a/vignettes/gkpubs.bib
+++ /dev/null
@@ -1,2259 +0,0 @@
-% A bibtex-format file for papers by or coauthored with Gary King
-%
-% rules used for abbreviations:
-%
-% -if one author: use last name and last 2 digits of the year: King99.
-% -if multiple authors, use 1st 3 letters of each of UP TO the first three
-% authors and the last 2 digits of the year: KinTomWit00.
-% -if necessary add lower-case letters for multiple entries in a year:
-% King02, King02b (the first one should NOT have an 'a' afterwards)
-% -No string abbreviations are used
-%
-% entries are in separate sections (books, articles, software, data)
-% in reverse chronical order
-%
-% copies of all papers, articles, data, and software, and some books,
-% are available at http://gking.harvard.edu/
-
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-% Books
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-
- at book{KinSchNie09,
- editor = {Gary King and Kay Schlozman and Norman Nie},
- title = {The Future of Political Science: 100 Perspectives},
- publisher = {Routledge Press},
- address = {New York},
- year = {2009}
-}
-
- at book{GirKin08,
- author = {Federico Girosi and Gary King},
- title = {Demographic Forecasting},
- publisher = {Princeton University Press},
- year = {2008},
- address = {Princeton},
- note = {{http://gking.harvard.edu/files/smooth/}}
-}
-
- at book{KinRosTan04,
- editor = {Gary King and Ori Rosen and Martin A. Tanner},
- title = {Ecological Inference: New Methodological Strategies},
- publisher = {Cambridge University Press},
- year = {2004},
- address = {New York},
- note = {{http://gking.harvard.edu/files/abs/ecinf04-abs.shtml}}
-}
-
- at book{King97,
- author = {Gary King},
- title = {A Solution to the Ecological Inference Problem:
- Reconstructing Individual Behavior from Aggregate
- Data},
- publisher = {Princeton University Press},
- year = {1997},
- address = {Princeton},
- note = {{http://gking.harvard.edu/eicamera/kinroot.html}}
-}
-
- at book{KinKeoVer94,
- author = {Gary King and Robert O. Keohane and Sidney Verba},
- title = {Designing Social Inquiry: Scientific Inference in
- Qualitative Research},
- publisher = {Princeton University Press},
- year = {1994},
- address = {Princeton},
- note = {{http://www.pupress.princeton.edu/titles/5458.html}}
-}
-
- at book{King89,
- author = {Gary King},
- title = {Unifying Political Methodology: The Likelihood
- Theory of Statistical Inference},
- publisher = {Michigan University Press},
- year = 1989,
- address = {Ann Arbor}
-}
-
- at book{KinRag88,
- author = {Gary King and Lyn Ragsdale},
- title = {The Elusive Executive: Discovering Statistical
- Patterns in the Presidency},
- publisher = {Congressional Quarterly Press},
- year = {1988},
- address = {Washington, D.C}
-}
-
- at book{BraHarKin89,
- author = {Paul Brace and Christine Harrington and Gary King},
- title = {The Presidency in American Politics},
- publisher = {New York University Press},
- year = {1989},
- address = {New York and London}
-}
-
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-% Articles
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-
- at Article{SonKin11,
- author = {Samir Soneji and Gary King},
- title = {Statistical Security for Social Security},
- journal = {Demography},
- year = 2011,
- note = {{http://gking.harvard.edu/files/abs/ssc-abs.shtml}}
-}
-
- at Article{,
- author = {Gary King and Richard Nielsen and Carter Coberley
- and James Pope and Aaron Wells},
- title = {Avoiding Randomization Failure in Program
- Evaluation},
- journal = {Population Health Management},
- year = 2011,
- volume = 14,
- number = 1,
- pages = {S11-S22},
- note = {{http://gking.harvard.edu/gking/files/mhs.pdf}}
-}
-
- at Article{KinNieCob11,
- author = {Gary King and Richard Nielsen and Carter Coberley
- and James Pope and Aaron Wells},
- title = {Comparative Effectiveness of Matching Methods for
- Causal Inference},
- journal = { },
- year = {2011},
- OPTkey = {},
- OPTvolume = {},
- OPTnumber = {},
- OPTpages = {},
- OPTmonth = {},
- OPTnote = {{http://gking.harvard.edu/files/abs/psparadox-abs.shtml}},
- OPTannote = {}
-}
-
- at Article{SteKinShi10,
- author = {Gretchen Stevens, Gary King, and Kenji Shibuya},
- title = {Deaths From Heart Failure: Using Coarsened Exact
- Matching to Correct Cause of Death Statistics},
- journal = {Population Health Metrics},
- year = 2010,
- volume = 8,
- number = 6,
- note = {{http://gking.harvard.edu/files/abs/heartfcem-abs.shtml}}
-}
-
- at Article{GriKin10,
- author = {Justin Grimmer and Gary King},
- title = {Quantitative Discovery from Qualitative Information:
- A General-Purpose Document Clustering Methodology},
- journal = { },
- year = {2010},
- note = {{http://gking.harvard.edu/files/abs/discov-abs.shtml}}
-}
-
- at Article{GriKin10b,
- author = {Justin Grimmer and Gary King},
- title = {A General Purpose Computer-Assisted Document
- Clustering Methodology},
- journal = { },
- year = {2010},
- note =
- {{http://gking.harvard.edu/files/abs/discovm-abs.shtml}}
-}
-
- at Article{IacKinPor11,
- author = {Stefano M. Iacus and Gary King and Giuseppe Porro},
- title = {Multivariate Matching Methods That are Monotonic
- Imbalance Bounding},
- journal = {Journal of the American Statistical Association},
- year = {In press},
- note = {{http://gking.harvard.edu/files/abs/cem-math-abs.shtml}}
-}
-
- at article{HopKin10,
- author = {Daniel Hopkins and Gary King},
- title = {Improving Anchoring Vignettes: Designing Surveys to
- Correct Interpersonal Incomparability},
- journal = {Public Opinion Quarterly},
- year = {2010},
- pages = {1-22},
- note = {{http://gking.harvard.edu/files/abs/implement-abs.shtml}}
-}
-
- at Article{KinLuShi10,
- author = {Gary King and Ying Lu and Kenji Shibuya},
- title = {Designing Verbal Autopsy Studies},
- journal = {Population Health Metrics},
- year = 2010,
- volume = 8,
- number = 19,
- note = {http://gking.harvard.edu/files/abs/desva-abs.shtml}
-}
-
- at article{LazPenAda09,
- author = {Lazer, David and Pentland, Alex and Adamic, Lada and
- Aral, Sinan and Barabasi, Albert-Laszlo and Brewer,
- Devon and Christakis, Nicholas and Contractor,
- Noshir and Fowler, James and Gutmann, Myron and
- Jebara, Tony and King, Gary and Macy, Michael and
- Roy, Deb and Van Alstyne, Marshall},
- title = {{SOCIAL SCIENCE: Computational Social Science}},
- journal = {Science},
- volume = {323},
- number = {5915},
- pages = {721-723},
- year = {2009},
- note = {{http://gking.harvard.edu/files/abs/LazPenAda09-abs.shtml}}
-}
-
- at Article{AbrBolGut09,
- author = {Mark Abrahamson and Kenneth A. Bollen and Myron
- Gutmann and Gary King and Amy M. Pienta},
- title = {Preserving Data for Long Term Analyses},
- journal = {Historical Social Research},
- year = {2009},
- OPTkey = {},
- OPTvolume = {},
- OPTnumber = {},
- OPTpages = {},
- OPTmonth = {Summer, forthcoming},
- OPTnote = {},
- OPTannote = {}
-}
-
- at article{KinGakIma09,
- Author = {Gary King and Emmanuela Gakidou and Kosuke Imai and
- Jason Lakin and Ryan T. Moore and Clayton Nall and
- Nirmala Ravishankar and Manett Vargas and Martha
- Mar{\'i}a T{\'e}llez-Rojo and Juan Eugenio
- Hern{\'a}ndez {\'A}vila and Mauricio Hern{\'a}ndez
- {\'A}vila and H{\'e}ctor Hern{\'a}ndez Llamas},
- title = {Public Policy for the Poor? A Randomised Assessment
- of the Mexican Universal Health Insurance Programme},
- journal = {The Lancet},
- volumne = {373},
- year = {2009},
- note = {{http://gking.harvard.edu/files/abs/spi-abs.shtml}}
-}
-
-
- at Article{KinSon09,
- author = {Gary King and Samir Soneji},
- title = {The Future of Death in America},
- journal = {},
- year = 2009,
- note = {{http://gking.harvard.edu/files/abs/mort-abs.shtml}}
-}
-
- at Article{IacKinPor11,
- author = {Stefano M. Iacus and Gary King and Giuseppe Porro},
- title = {Causal Inference Without Balance Checking: Coarsened
- Exact Matching},
- journal = {Political Analysis},
- year = {2011, in press},
- note = {{http://gking.harvard.edu/files/abs/cem-plus-abs.shtml}}
-}
-
- at article{ImaKinStu08,
- author = {Kosuke Imai and Gary King and Elizabeth Stuart},
- title = {Misunderstandings Among Experimentalists and
- Observationalists about Causal Inference},
- journal = {Journal of the Royal Statistical Society, {S}eries
- {A}},
- volume = {171, part 2},
- year = {2008},
- pages = {481--502},
- note =
- {{http://gking.harvard.edu/files/abs/matchse-abs.shtml}}
-}
-
- at article{uImaKinStu08,
- author = {Kosuke Imai and Gary King and Elizabeth Stuart},
- title = {Misunderstandings Among Experimentalists and
- Observationalists about Causal Inference},
- journal = {Journal of the Royal Statistical Society, {S}eries
- {A}},
- volume = {171, part 2},
- year = {2008},
- pages = {481--502}
-}
-
- at article{KinLu08,
- author = {Gary King and Ying Lu},
- title = {Verbal Autopsy Methods with Multiple Causes of
- Death},
- journal = {Statistical Science},
- volume = {23},
- number = {1},
- year = {2008},
- pages = {78--91},
- note = {{http://gking.harvard.edu/files/abs/vamc-abs.shtml}}
-}
-
- at article{AltKin07,
- author = {Micah Altman and Gary King},
- title = {A Proposed Standard for the Scholarly Citation of
- Quantitative Data },
- journal = {D-Lib Magazine},
- volume = {13},
- year = {2007},
- month = {March / April},
- number = {3/4},
- note = {{http://gking.harvard.edu/files/abs/cite-abs.shtml}}
-}
-
- at article{GroKin07,
- author = {Bernard Grofman and Gary King},
- title = {The Future of Partisan Symmetry as a Judicial Test
- for Partisan Gerrymandering after LULAC v. Perry},
- journal = {Election Law Journal},
- volume = {6},
- year = {2007},
- pages = {2-35},
- month = {January},
- number = {1},
- note = {{http://gking.harvard.edu/files/abs/jp-abs.shtml}}
-}
-
- at article{uHoImaKin07,
- author = {Daniel Ho and Kosuke Imai and Gary King and
- Elizabeth Stuart},
- title = {Matching as Nonparametric Preprocessing for Reducing
- Model Dependence in Parametric Causal Inference},
- journal = {Political Analysis},
- year = {2007},
- volume = {15},
- pages = {199--236}
-}
-
- at article{HoImaKin07,
- author = {Daniel Ho and Kosuke Imai and Gary King and
- Elizabeth Stuart},
- title = {Matching as Nonparametric Preprocessing for Reducing
- Model Dependence in Parametric Causal Inference},
- journal = {Political Analysis},
- year = {2007},
- volume = {15},
- pages = {199--236},
- note = {{http://gking.harvard.edu/files/abs/matchp-abs.shtml}}
-}
-
- at article{HopKin10b,
- author = {Daniel Hopkins and Gary King},
- title = {A Method of Automated Nonparametric Content Analysis
- for Social Science},
- journal = {American Journal of Political Science},
- year = {2010},
- volume = {54},
- number = {1},
- month = {January},
- pages = {229--247},
- note = {http://gking.harvard.edu/files/abs/words-abs.shtml}
-}
-
- at article{ImaKinLau07,
- author = {Kosuke Imai and Gary King and Olivia Lau},
- title = {Toward A Common Framework for Statistical Analysis
- and Development},
- journal = {Journal of Computational Graphics and Statistics},
- volume = 17,
- number = 4,
- pages = {1--22},
- year = 2008,
- note = {{http://gking.harvard.edu/files/abs/z-abs.shtml}}
-}
-
- at article{ImaKinNal09d,
- author = {Kosuke Imai and Gary King and Clayton Nall},
- title = {Matched Pairs and the Future of Cluster-Randomized
- Experiments: A Rejoinder},
- journal = {Statistical Science},
- volume = {24},
- number = {1},
- pages = {64--72},
- year = {2009},
- note =
- {{http://gking.harvard.edu/files/abs/cluster-abs.shtml}}
-}
-
- at article{ImaKinNal09,
- author = {Kosuke Imai and Gary King and Clayton Nall},
- title = {The Essential Role of Pair Matching in
- Cluster-Randomized Experiments, with Application to
- the Mexican Universal Health Insurance Evaluation},
- journal = {Statistical Science},
- volume = {24},
- number = {1},
- pages = {29--53},
- year = {2009},
- note =
- {{http://gking.harvard.edu/files/abs/cluster-abs.shtml}}
-}
-
- at article{uImaKinNal09,
- author = {Kosuke Imai and Gary King and Clayton Nall},
- title = {The Essential Role of Pair Matching in
- Cluster-Randomized Experiments, with Application to
- the Mexican Universal Health Insurance Evaluation},
- journal = {Statistical Science},
- volume = {24},
- number = {1},
- pages = {29--53},
- year = {2009}
-}
-
- at article{King07,
- author = {Gary King},
- title = {An Introduction to the Dataverse Network as an
- Infrastructure for Data Sharing},
- journal = {Sociological Methods and Research},
- year = {2007},
- volume = {36},
- number = {2},
- pages = {173--199},
- note = {{http://gking.harvard.edu/files/abs/dvn-abs.shtml}}
-}
-
- at inbook{King09b,
- author = {Gary King},
- chapter = {The Changing Evidence Base of Political Science
- Research},
- title = {The Future of Political Science: 100 Perspectives},
- publisher = {Routledge Press},
- address = {New York},
- year = {2009, forthcoming},
- editor = {Gary King and Kay Schlozman and Norman Nie},
- note = {{http://gking.harvard.edu/files/abs/evbase-abs.shtml}}
-}
-
- at inbook{King09c,
- author = {Gary King and Kay Schlozman and Norman Nie},
- chapter = {An Introduction to the Future of Political Science},
- title = {The Future of Political Science: 100 Perspectives},
- publisher = {Routledge Press},
- address = {New York},
- year = {2009, forthcoming},
- editor = {Gary King and Kay Schlozman and Norman Nie}
-}
-
- at article{KinGakRav07,
- Author = {Gary King and Emmanuela Gakidou and Nirmala
- Ravishankar and Ryan T. Moore and Jason Lakin and
- Manett Vargas and Martha Mar{\'i}a T{\'e}llez-Rojo
- and Juan Eugenio Hern{\'a}ndez {\'A}vila and
- Mauricio Hern{\'a}ndez {\'A}vila and H{\'e}ctor
- Hern{\'a}ndez Llamas},
- title = {A `Politically Robust' Experimental Design for
- Public Policy Evaluation, with Application to the
- Mexican Universal Health Insurance Program},
- journal = {Journal of Policy Analysis and Management},
- volume = {26},
- year = {2007},
- pages = {479-506},
- number = {3},
- note = {{http://gking.harvard.edu/files/abs/spd-abs.shtml}}
-}
-
- at article{KinWan07,
- author = {Gary King and Jonathan Wand},
- title = {Comparing Incomparable Survey Responses: New Tools
- for Anchoring Vignettes},
- journal = {Political Analysis},
- volume = {15},
- year = {2007},
- pages = {46-66},
- month = {Winter},
- number = {1},
- note = {{http://gking.harvard.edu/files/abs/c-abs.shtml}}
-}
-
- at article{KinZen07,
- author = {Gary King and Langche Zeng},
- title = {When Can History Be Our Guide? The Pitfalls of
- Counterfactual Inference},
- journal = {International Studies Quarterly},
- year = {2007},
- pages = {183-210},
- month = {March},
- note = {{http://gking.harvard.edu/files/abs/counterf-abs.shtml}}
-}
-
- at article{uKinZen07,
- author = {Gary King and Langche Zeng},
- title = {When Can History Be Our Guide? The Pitfalls of
- Counterfactual Inference},
- journal = {International Studies Quarterly},
- year = {2007},
- pages = {183-210},
- month = {March}
-}
-
- at article{KinZen07b,
- author = {Gary King and Langche Zeng},
- title = {Detecting Model Dependence in Statistical Inference:
- A Response},
- journal = {International Studies Quarterly},
- volume = {51},
- year = {2007},
- pages = {231-241},
- month = {March},
- note = {{http://gking.harvard.edu/files/abs/counterf-abs.shtml}}
-}
-
- at article{WanKinLau07,
- author = {Jonathan Wand and Gary King and Olivia Lau},
- title = {Anchors: Software for Anchoring Vignettes Data},
- journal = {Journal of Statistical Software},
- year = {2007, forthcoming}
-}
-
- at inbook{EpsHoKin06,
- author = {Lee Epstein and Daniel E. Ho and Gary King and
- Jeffrey A. Segal},
- title = {Principles and Practice in American Politics:
- Classic and Contemporary Readings},
- chapter = {The Effect of War on the Supreme Court},
- year = {2006},
- publisher = {Congressional Quarterly Press},
- edition = {3rd},
- address = {Washington, D.C.},
- editor = {Samuel Kernell and Steven S. Smith},
- note = {{http://gking.harvard.edu/files/abs/crisis-abs.shtml}}
-}
-
- at article{GakKin06,
- author = {Emmanuela Gakidou and Gary King},
- title = {Death by Survey: Estimating Adult Mortality without
- Selection Bias from Sibling Survival Data from
- Sibling Survival Data},
- journal = {Demography},
- volume = 43,
- year = 2006,
- pages = {569--585},
- month = {August},
- number = 3,
- note = {{http://gking.harvard.edu/files/abs/deathbys-abs.shtml}}
-}
-
- at article{HonKin10,
- author = {James Honaker and Gary King},
- title = {What to do About Missing Values in Time Series
- Cross-Section Data},
- journal = {American Journal of Political Science},
- year = {2010},
- volume = {54},
- number = {2},
- month = {April},
- pages = {561--581},
- note = {{http://gking.harvard.edu/files/abs/pr-abs.shtml}}
-}
-
- at article{King06,
- author = {Gary King},
- title = {{Publication, Publication}},
- journal = {PS: Political Science and Politics},
- volume = {39},
- year = {2006},
- pages = {119--125},
- month = {January},
- number = {01},
- note =
- {{http://gking.harvard.edu/files/abs/paperspub-abs.shtml}}
-}
-
- at inbook{KinRosTan06,
- author = {Gary King and Ori Rosen and Martin Tanner},
- title = {The New Palgrave Dictionary of Economics},
- chapter = {Ecological Inference},
- year = {2006},
- edition = {2nd},
- editor = {Larry Blume and Steven N. Durlauf},
- note =
- {{http://gking.harvard.edu/files/abs/newintro-abs.shtml}}
-}
-
- at article{KinZen06,
- author = {Gary King and Langche Zeng},
- title = {The Dangers of Extreme Counterfactuals},
- journal = {Political Analysis},
- volume = {14},
- year = 2006,
- pages = {131--159},
- number = {2},
- note =
- {{http://gking.harvard.edu/files/abs/counterft-abs.shtml}}
-}
-
- at article{GirKin07,
- author = {Federico Girosi and Gary King},
- title = {Understanding the Lee-Carter Mortality Forecasting
- Method},
- year = 2007,
- note = {{http://gking.harvard.edu/files/abs/lc-abs.shtml}}
-}
-
- at article{EpsHoKin05,
- author = {Lee Epstein and Daniel E. Ho and Gary King, and
- Jeffrey A. Segal},
- title = {The Supreme Court During Crisis: How War Affects
- only Non-War Cases},
- journal = {New York University Law Review},
- volume = {80},
- year = {2005},
- pages = {1--116},
- month = {April},
- number = {1},
- note = {{http://gking.harvard.edu/files/abs/crisis-abs.shtml}}
-}
-
- at article{StoKinZen05,
- author = {Heather Stoll and Gary King and Langchee Zeng},
- title = {WhatIf: Software for Evaluating Counterfactuals},
- journal = {Journal of Statistical Software},
- volume = {15},
- year = {2005},
- number = {4},
- note = {{http://www.jstatsoft.org/index.php?vol=15}}
-}
-
- at article{BecKinZen04,
- author = {Nathaniel Beck and Gary King and Langche Zeng},
- title = {Theory and Evidence in International Conflict:
- Response to de Marchi, Gelpi, and Grynaviski},
- journal = apsr,
- volume = {98},
- year = {2004},
- pages = {379-389},
- month = {May},
- number = {2},
- note =
- {{http://gking.harvard.edu/files/abs/toe-resp-abs.shtml}}
-}
-
- at inbook{GelKatKin04,
- author = {Andrew Gelman and Jonathan Katz and Gary King},
- title = {Rethinking the Vote: The Politics and Prospects of
- American Electoreal Reform},
- chapter = {Chapter 5, Empirically Evaluating the Electoral
- College},
- year = {2004},
- publisher = {Oxford University Press},
- pages = {75-88},
- address = {New York},
- editor = {Ann N. Crigler and Marion R. Just and Edward
- J. McCaffery},
- note =
- {{http://gking.harvard.edu/files/abs/rethink-abs.shtml}}
-}
-
- at article{GilKin04,
- author = {Jeff Gill and Gary King},
- title = {What to do When Your Hessian is Not Invertible:
- Alternatives to Model Respecification in Nonlinear
- Estimation},
- journal = {Sociological Methods and Research},
- volume = {32},
- year = {2004},
- pages = {54-87},
- month = {August},
- number = {1},
- note = {{http://gking.harvard.edu/files/abs/help-abs.shtml}}
-}
-
- at article{ImaKin04,
- author = {Kosuke Imai and Gary King},
- title = {Did Illegal Overseas Absentee Ballots Decide the
- 2000 U.S. Presidential Election?},
- journal = {Perspectives on Politics},
- volume = {2},
- year = {2004},
- pages = {537--549},
- month = {September},
- number = {3},
- note =
- {{http://gking.harvard.edu/files/abs/ballots-abs.shtml}}
-}
-
- at article{King04,
- author = {Gary King},
- title = {EI: A Program for Ecological Inference},
- journal = {Journal of Statistical Software},
- volume = {11},
- year = {2004},
- number = {7}
-}
-
- at article{King04b,
- author = {Gary King},
- title = {Finding New Information for Ecological Inference
- Models: A Comment on Jon Wakefield, "Ecological
- Inference in 2 X 2 Tables"},
- journal = {Journal of the Royal Statistical Society},
- volume = {167},
- year = {2004},
- pages = {437},
- number = {Series A}
-}
-
- at inbook{KinRosTan04b,
- author = {Gary King and Ori Rosen and Martin Tanner},
- title = {Ecological Inference: New Methodological Strategies},
- chapter = {Information in Ecological Inference: An
- Introduction},
- year = {2004},
- publisher = {Cambridge University Press},
- address = {New York},
- editor = {Gary King and Ori Rosen and Martin Tanner}
-}
-
- at inbook{KinZen04,
- author = {Gary King and Langche Zeng},
- title = {Encyclopedia of Biopharmaceutical Statistics},
- chapter = {Inference in Case-Control Studies},
- year = {2004},
- publisher = {Marcel Dekker},
- edition = {2nd},
- address = {New York},
- editor = {Shein-Chung Chow},
- note = {{http://gking.harvard.edu/files/abs/1s-enc-abs.shtml}}
-}
-
- at article{AdoKin03,
- author = {Christopher Adolph and Gary King},
- title = {Analyzing Second Stage Ecological Regressions},
- journal = {Political Analysis},
- volume = {11},
- year = {2003},
- pages = {65-76},
- month = {Winter},
- number = {1}
-}
-
- at article{AdoKinHer03,
- author = {Christopher Adolph and Gary King, with Michael
- C. Herron and Kenneth W. Shotts},
- title = {A Consensus on Second Stage Analyses in Ecological
- Inference Models},
- journal = {Political Analysis},
- volume = {11},
- year = {2003},
- pages = {86--94},
- month = {Winter},
- number = {1},
- note = {{http://gking.harvard.edu/files/abs/akhs-abs.shtml}}
-}
-
- at article{EpsKin03,
- author = {Lee Epstein and Gary King},
- title = {Building An Infrastructure for Empirical Research in
- the Law [with comments from four law school deans]},
- journal = {Journal of Legal Education},
- volume = {53},
- year = {2003},
- pages = {311--320},
- number = {311},
- note = {{http://gking.harvard.edu/files/abs/infra-abs.shtml}}
-}
-
- at inbook{GakKin03,
- author = {Emmanuela Gakidou and Gary King},
- title = {Health Systems Performance Assessment: Debates,
- Methods and Empiricism},
- chapter = {Chapter 36, Determinants of Inequality in Child
- Survival: Results from 39 Countries},
- publisher = {World Health Organization},
- pages = {497-502},
- address = {Geneva},
- editor = {Chrisopher Murray and David B. Evans}
-}
-
- at inbook{GilKin03,
- author = {Jeff Gill and Gary King},
- title = {Numerical Issues in Statistical Computing for the
- Social Scientist},
- chapter = {Chapter 6, Numerical Issues Involved in Inverting
- Hessian Matrices},
- year = {2003},
- publisher = {John Wiley and Sons, Inc.},
- pages = {143-176},
- address = {Hoboken, NJ},
- editor = {Micah Altman and Jeff Gill and Michael P. McDonald}
-}
-
- at article{King03,
- author = {Gary King},
- title = {The Future of Replication},
- journal = {International Studies Perspectives},
- volume = {4},
- year = {2003},
- pages = {443--499},
- month = {February},
- number = 1,
- note =
- {{http://gking.harvard.edu/files/abs/replvdc-abs.shtml}}
-}
-
- at article{KinLow03,
- author = {Gary King and Will Lowe},
- title = {An Automated Information Extraction Tool For
- International Conflict Data with Performance as Good
- as Human Coders: A Rare Events Evaluation Design},
- journal = {International Organization},
- volume = {57},
- year = {2003},
- pages = {617-642},
- month = {July},
- number = {3},
- note = {{http://gking.harvard.edu/files/abs/infoex-abs.shtml}}
-}
-
- at article{KinMurSal04,
- author = {Gary King and Christopher J.L. Murray and Joshua
- A. Salomon and Ajay Tandon},
- title = {Enhancing the Validity and Cross-cultural
- Comparability of Measurement in Survey Research},
- journal = {American Political Science Review},
- volume = {98},
- year = {2004},
- pages = {191--207},
- month = {February},
- number = {1},
- note = {{http://gking.harvard.edu/files/abs/vign-abs.shtml}}
-}
-
- at article{KinRosTan07,
- author = {Gary King and Ori Rosen and Martin Tanner and
- Alexander F. Wagner.},
- title = {Ordinary Economic Voting Behavior in the
- Extraordinary Election of Adolf Hitler},
- year = {2007},
- note = {{http://gking.harvard.edu/files/abs/naziV-abs.shtml}}
-}
-
- at inbook{KinZen03,
- author = {Gary King and Langche Zeng},
- title = {Inference in Case-Control Studies},
- year = {2003},
- publisher = {Marcel Dekker},
- volume = {2nd edition},
- address = {New York},
- editor = {Shein-Chung Chow, ed.},
- journal = {Encyclopedia of Biopharmaceutical Statistics}
-}
-
- at article{LowKin03,
- author = {Will Lowe and Gary King },
- title = {Some Statistical Methods for Evaluating Information
- Extraction Systems},
- journal = {Proceedings of the 10th Conference of the European
- Chapter of the Association for Computational
- Linguistics},
- year = {2003},
- pages = {19-26}
-}
-
- at article{TomKinZen03,
- author = {Michael Tomz and Gary King and Langche Zeng},
- title = {ReLogit: Rare Events Logistic Regression},
- journal = {Journal of Statistical Software},
- volume = {8},
- year = {2003},
- number = {2},
- note = {{http://gking.harvard.edu/stats.shtml#relogit}}
-}
-
- at article{TomWitKin03,
- author = {Michael Tomz and Jason Wittenberg and Gary King},
- title = {CLARIFY: Software for Interpreting and Presenting
- Statistical Results},
- journal = {Journal of Statistical Software},
- volume = {8},
- year = {2003},
- number = {1},
- note = {{http://gking.harvard.edu/stats.shtml}}
-}
-
- at article{EpsKin02,
- author = {Lee Epstein and Gary King},
- title = {The Rules of Inference},
- journal = {University of Chicago Law Review},
- volume = {69},
- year = {2002},
- pages = {1--209},
- month = {Winter},
- number = {1},
- note = {{http://gking.harvard.edu/files/abs/rules-abs.shtml}}
-}
-
- at article{EpsKin02b,
- author = {Lee Epstein and Gary King},
- title = {Empirical Research and The Goals of Legal
- Scholarship: A Response},
- journal = {University of Chicago Law Review},
- volume = {69},
- year = {2002},
- pages = {1--209},
- month = {Winter},
- number = {1},
- note = {{http://gking.harvard.edu/files/abs/rules-abs.shtml}}
-}
-
- at article{GakKin02,
- author = {Emmanuela Gakidou and Gary King},
- title = {Measuring Total Health Inequality: Adding Individual
- Variation to Group-Level Differences},
- journal = {BioMed Central: International Journal for Equity in
- Health},
- volume = {1},
- year = 2002,
- month = {August},
- number = 3,
- note = {{http://gking.harvard.edu/files/abs/ebb-abs.shtml}}
-}
-
- at article{HonKinKat02,
- author = {James Honaker and Gary King and Jonathan N. Katz},
- title = {A Fast, Easy, and Efficient Estimator for Multiparty
- Electoral Data},
- journal = {Political Analysis},
- volume = {10},
- year = {2002},
- pages = {84--100},
- month = {Winter},
- number = {1},
- note = {{http://gking.harvard.edu/files/abs/trip-abs.shtml}}
-}
-
- at article{King02b,
- author = {Gary King},
- title = {Isolating Spatial Autocorrelation, Aggregation Bias,
- and Distributional Violations in Ecological
- Inference},
- journal = {Political Analysis},
- volume = {10},
- year = {2002},
- pages = {298--300},
- month = {Summer},
- number = {3},
- note = {{http://gking.harvard.edu/files/abs/ac-abs.shtml}}
-}
-
- at article{KinMur02,
- author = {Gary King and Christopher J.L. Murray},
- title = {Rethinking Human Security},
- journal = {Political Science Quarterly},
- volume = {116},
- year = {2002},
- pages = {585--610},
- month = {Winter},
- number = {4},
- note = {{http://gking.harvard.edu/files/abs/hs-abs.shtml}}
-}
-
- at article{KinZen02,
- author = {Gary King and Langche Zeng},
- title = {Improving Forecasts of State Failure},
- journal = {World Politics},
- volume = 53,
- year = 2002,
- pages = {623--658},
- month = {July},
- number = 4 ,
- note = {{http://gking.harvard.edu/files/abs/civil-abs.shtml}}
-}
-
- at article{KinZen02b,
- author = {Gary King and Langche Zeng},
- title = {Estimating Risk and Rate Levels, Ratios, and
- Differences in Case-Control Studies},
- journal = {Statistics in Medicine},
- volume = 21,
- year = 2002,
- pages = {1409--1427},
- note = {{http://gking.harvard.edu/files/abs/1s-abs.shtml}}
-}
-
- at article{MurKinLop02,
- author = {Christopher J.L. Murray and Gary King and Alan
- D. Lopez and Niels Tomijima and Etienne Krug},
- title = {Armed Conflict as a Public Health Problem},
- journal = {BMJ (British Medical Journal)},
- volume = {324},
- year = {2002},
- pages = {346--349},
- month = {February 9},
- note =
- {{http://gking.harvard.edu/files/abs/armedph-abs.shtml}}
-}
-
- at article{AltAndDig01a,
- author = {Micah Altman and Leonid Andreev and Mark Diggory and
- Gary King and Daniel L. Kiskis and Elizabeth Kolster
- and M. Krot and Sidney Verba},
- title = {A Digital Library for the Dissemination and
- Replication of Quantitative Social Science Research:
- The Virtual Data Center},
- journal = {Social Science Computer Review},
- volume = 19,
- year = 2001,
- pages = {458--470},
- month = {Winter},
- number = 4,
- note =
- {{http://gking.harvard.edu/files/abs/vdcwhitepaper-abs.shtml}}
-}
-
- at article{AltAndDig01b,
- author = {Micah Altman and Leonid Andreev and Mark Diggory and
- Gary King and Daniel L. Kiskis and Elizabeth Kolster
- and M. Krot and Sidney Verba},
- title = {An Overview of the Virtual Data Center Project and
- Software},
- journal = {JCDL '01: First Joint Conference on Digital
- Libraries},
- year = 2001,
- pages = {203-204},
- note = {{http://gking.harvard.edu/files/abs/jcdl01-abs.shtml}}
-}
-
- at article{AltKinSig01,
- author = {James E. Alt and Gary King and Curtis Signorino},
- title = {Aggregation Among Binary, Count, and Duration
- Models: Estimating the Same Quantities from
- Different Levels of Data},
- journal = {Political Analysis},
- volume = {9},
- year = {2001},
- pages = {21--44},
- month = {Winter},
- number = {1},
- note = {{http://gking.harvard.edu/files/abs/abcd-abs.shtml}}
-}
-
- at article{King01,
- author = {Gary King},
- title = {Proper Nouns and Methodological Propriety: Pooling
- Dyads in International Relations Data},
- journal = {International Organization},
- volume = {55},
- year = {2001},
- pages = {497--507},
- month = {Fall},
- number = {2},
- note = {{http://gking.harvard.edu/files/abs/pool-abs.shtml}}
-}
-
- at article{KinHonJos01,
- author = {Gary King and James Honaker and Anne Joseph and
- Kenneth Scheve},
- title = {Analyzing Incomplete Political Science Data: An
- Alternative Algorithm for Multiple Imputation},
- journal = {American Political Science Review},
- volume = 95,
- year = 2001,
- pages = {49--69},
- month = {March},
- number = 1 ,
- note = {{http://gking.harvard.edu/files/abs/evil-abs.shtml}}
-}
-
- at article{KinZen01,
- author = {Gary King and Langche Zeng},
- title = {Logistic Regression in Rare Events Data},
- journal = {Political Analysis},
- volume = 9,
- year = 2001,
- pages = {137--163},
- month = {Spring},
- number = 2 ,
- note = {{http://gking.harvard.edu/files/abs/0s-abs.shtml}}
-}
-
- at article{KinZen01b,
- author = {Gary King and Langche Zeng},
- title = {Explaining Rare Events in International Relations},
- journal = {International Organization},
- volume = 55,
- year = 2001,
- pages = {693--715},
- month = {Summer},
- number = 3 ,
- note = {{http://gking.harvard.edu/files/abs/baby0s-abs.shtml}}
-}
-
- at article{RosJiaKin01,
- author = {Ori Rosen and Wenxin Jiang and Gary King and Martin
- A. Tanner},
- title = {Bayesian and Frequentist Inference for Ecological
- Inference: The $R \times C$ Case},
- journal = {Statistica Neerlandica},
- volume = 55,
- year = 2001,
- pages = {134--156},
- number = 2 ,
- note = {{http://gking.harvard.edu/files/abs/rosen-abs.shtml}}
-}
-
- at article{BecKinZen00,
- author = {Nathaniel Beck and Gary King and Langche Zeng},
- title = {Improving Quantitative Studies of International
- Conflict},
- journal = {American Political Science Review},
- volume = 94,
- year = 2000,
- pages = {21--36},
- month = {March},
- number = 1 ,
- note = {{http://gking.harvard.edu/files/abs/improv-abs.shtml}}
-}
-
- at article{King00,
- author = {Gary King},
- title = {Geography, Statistics, and Ecological Inference},
- journal = {Annals of the Association of American Geographers},
- volume = {90},
- year = {2000},
- pages = {601--606},
- month = {September},
- number = {3},
- note = {{http://gking.harvard.edu/files/abs/geog-abs.shtml}}
-}
-
- at article{KinTomWit00,
- author = {Gary King and Michael Tomz and Jason Wittenberg},
- title = {Making the Most of Statistical Analyses: Improving
- Interpretation and Presentation},
- journal = {American Journal of Political Science},
- volume = 44,
- year = 2000,
- pages = {341--355},
- month = {April},
- number = 2,
- note = {{http://gking.harvard.edu/files/abs/making-abs.shtml}}
-}
-
- at article{GelKinLiu99,
- author = {Andrew Gelman and Gary King and Chuanhai Liu},
- title = {Not Asked and Not Answered: Multiple Imputation for
- Multiple Surveys},
- journal = {Journal of the American Statistical Association},
- volume = 93,
- year = 1999,
- pages = {846--857},
- month = {September},
- number = 433 ,
- note = {{http://gking.harvard.edu/files/abs/not-abs.shtml}}
-}
-
- at article{GelKinLiu99b,
- author = {Andrew Gelman and Gary King and Chuanhai Liu},
- title = {Rejoinder},
- journal = {Journal of the American Statistical Association},
- volume = 93,
- year = 1999,
- pages = {869--874},
- month = {September},
- number = 433 ,
- note = {{http://gking.harvard.edu/files/abs/not-abs.shtml}}
-}
-
- at article{KatKin99,
- author = {Jonathan Katz and Gary King},
- title = {A Statistical Model for Multiparty Electoral Data},
- journal = {American Political Science Review},
- volume = 93,
- year = 1999,
- pages = {15--32},
- month = {March},
- number = {1},
- note =
- {{http://gking.harvard.edu/files/abs/multiparty-abs.shtml}}
-}
-
- at article{King99,
- author = {Gary King},
- title = {The Future of Ecological Inference Research: A Reply
- to Freedman et al.},
- journal = {Journal of the American Statistical Association},
- volume = {94},
- year = {1999},
- pages = {352-355},
- month = {March},
- number = {445},
- note = {{http://gking.harvard.edu/files/abs/reply-abs.shtml}}
-}
-
- at article{KinLav99,
- author = {Gary King and Michael Laver},
- title = {Many Publications, but Still No Evidence},
- journal = {Electoral Studies},
- volume = {18},
- year = {1999},
- pages = {597--598},
- month = {December},
- number = {4},
- note =
- {{http://gking.harvard.edu/files/abs/manypub-abs.shtml}}
-}
-
- at article{KinRosTan99,
- author = {Gary King and Ori Rosen and Martin A. Tanner},
- title = {Binomial-Beta Hierarchical Models for Ecological
- Inference},
- journal = {Sociological Methods and Research},
- volume = 28,
- year = 1999,
- pages = {61--90},
- month = {August},
- number = 1 ,
- note = {{http://gking.harvard.edu/files/abs/binom-abs.shtml}}
-}
-
- at article{LewKin99,
- author = {Jeffrey Lewis and Gary King},
- title = {No Evidence on Directional vs. Proximity Voting},
- journal = {Political Analysis},
- volume = {8},
- year = {1999},
- pages = {21--33},
- month = {August},
- number = {1},
- note =
- {{http://gking.harvard.edu/files/abs/spatial-abs.shtml}}
-}
-
- at article{GelKinBos98,
- author = {Andrew Gelman and Gary King and John Boscardin},
- title = {Estimating the Probability of Events that Have Never
- Occurred: When Is Your Vote Decisive?},
- journal = {Journal of the American Statistical Association},
- volume = {93},
- year = {1998},
- pages = {1--9},
- month = {March},
- number = {441},
- note =
- {{http://gking.harvard.edu/files/abs/estimatprob-abs.shtml}}
-}
-
- at article{KinPal98,
- author = {Gary King and Bradley Palmquist},
- title = {The Record of American Democracy, 1984-1990},
- journal = {Sociological Methods and Research},
- volume = {26},
- year = {1998},
- pages = {424--427},
- month = {February},
- number = {3},
- note = {{http://www.hmdc.harvard.edu/ROAD/}}
-}
-
- at article{BenKin96,
- author = {Kenneth Benoit and Gary King},
- title = {A Preview of EI and EzI: Programs for Ecological
- Inference},
- journal = {Social Science Computer Review},
- volume = {14},
- year = {1996},
- pages = {433--438},
- month = {Winter},
- number = {4},
- note =
- {{http://gking.harvard.edu/files/abs/preview-abs.shtml}}
-}
-
- at inbook{GelKin96,
- author = {Andrew Gelman and Gary King},
- title = {Advantages of Conflictual Redistricting},
- year = {1996},
- publisher = {Dartmouth Publishing Company},
- pages = {207--218 },
- address = {Aldershot, England},
- editor = {Iain McLean and David Butler, eds},
- note = {{http://gking.harvard.edu/files/abs/advant-abs.shtml}},
- journal = {Fixing the Boundary: Defining and Redefining
- Single-Member Electoral Districts}
-}
-
- at inbook{KinBruGel96,
- author = {Gary King and John Bruce and Andrew Gelman},
- title = {Racial Fairness in Legislative Redistricting},
- year = {1996},
- publisher = {Princeton University Press},
- editor = {Paul E. Peterson, ed.},
- note = {{http://gking.harvard.edu/files/abs/racial-abs.shtml}},
- journal = {Classifying by Race}
-}
-
- at article{King96,
- author = {Gary King},
- title = {Why Context Should Not Count},
- journal = {Political Geography },
- volume = {15},
- year = {1996},
- pages = {159--164},
- month = {February},
- number = {2},
- note = {{http://gking.harvard.edu/files/abs/contxt-abs.shtml}}
-}
-
- at article{KinSig96,
- author = {Gary King and Curtis S. Signorino},
- title = {The Generalization in the Generalized Event Count
- Model},
- journal = {Political Analysis},
- volume = 6,
- year = 1996,
- pages = {225--252},
- note =
- {{http://gking.harvard.edu/files/abs/generaliz-abs.shtml}}
-}
-
- at article{King95,
- author = {Gary King},
- title = {Replication, Replication},
- journal = {PS: Political Science and Politics},
- volume = {28},
- year = 1995,
- pages = {443--499},
- month = {September},
- number = 3,
- note =
- {{http://gking.harvard.edu/files/abs/replication-abs.shtml}}
-}
-
- at article{King95b,
- author = {Gary King},
- title = {A Revised Proposal, Proposal},
- journal = {PS: Political Science and Politics},
- volume = {XXVIII},
- year = 1995,
- pages = {494--499},
- month = {September},
- number = 3,
- note =
- {{http://gking.harvard.edu/files/abs/replication-abs.shtml}}
-}
-
- at article{KinKeoVer95,
- author = {Gary King and Robert O. Keohane and Sidney Verba},
- title = {The Importance of Research Design in Political
- Science},
- journal = {American Political Science Review},
- volume = {89},
- year = {1995},
- pages = {454--481 },
- month = {June},
- number = {2},
- note =
- {{http://gking.harvard.edu/files/abs/kkvresp-abs.shtml}}
-}
-
- at article{VosGelKin95,
- author = {D. Steven Voss and Andrew Gelman and Gary King},
- title = {Pre-Election Survey Methodology: Details From Nine
- Polling Organizations, 1988 and 1992},
- journal = {Public Opinion Quarterly},
- volume = {59},
- year = {1995},
- pages = {98--132},
- month = {Spring},
- number = {1},
- note =
- {{http://gking.harvard.edu/files/abs/preelection-abs.shtml}}
-}
-
- at article{WinSigKin95,
- author = {Rainer Winkelmann and Curtis Signorino and Gary
- King},
- title = {A Correction for an Underdispersed Event Count
- Probability Distribution},
- journal = {Political Analysis},
- year = {1995},
- pages = {215--228},
- note =
- {{http://gking.harvard.edu/files/abs/correction-abs.shtml}}
-}
-
- at article{AltKin94,
- author = {James E. Alt and Gary King},
- title = {Transfers of Governmental Power: The Meaning of Time
- Dependence},
- journal = {Comparative Political Studies},
- volume = {27},
- year = {1994},
- pages = {190--210},
- month = {July},
- number = {2},
- note =
- {{http://gking.harvard.edu/files/abs/transfers-abs.shtml}}
-}
-
- at article{GelKin94,
- author = {Andrew Gelman and Gary King},
- title = {A Unified Method of Evaluating Electoral Systems and
- Redistricting Plans},
- journal = {American Journal of Political Science},
- volume = 38,
- year = 1994,
- pages = {514--554},
- month = {May},
- number = 2,
- note =
- {{http://gking.harvard.edu/files/abs/writeit-abs.shtml}}
-}
-
- at article{GelKin94b,
- author = {Andrew Gelman and Gary King},
- title = {Enhancing Democracy Through Legislative
- Redistricting},
- journal = {American Political Science Review},
- volume = {88},
- year = {1994},
- pages = {541--559},
- month = {September},
- number = {3},
- note = {{http://gking.harvard.edu/files/abs/red-abs.shtml}}
-}
-
- at incollection{GelKin94c,
- author = {Andrew Gelman and Gary King},
- title = {Party Competition and Media Messages in
- U.S. Presidential Election Campaigns},
- booktitle = {The Parties Respond: Changes in the American Party
- System},
- publisher = {Westview Press},
- year = 1994,
- address = {Boulder, Colorado},
- editor = {L. Sandy Maisel},
- pages = {255-295},
- note =
- {{http://gking.harvard.edu/files/abs/partycomp-abs.shtml}}
-}
-
- at article{GelKin93,
- author = {Andrew Gelman and Gary King},
- title = {Why are American Presidential Election Campaign
- Polls so Variable when Votes are so Predictable?},
- journal = {British Journal of Political Science},
- volume = 23,
- year = 1993,
- pages = {409--451},
- month = {October},
- number = 1,
- note =
- {{http://gking.harvard.edu/files/abs/variable-abs.shtml}}
-}
-
- at inbook{King93,
- author = {Gary King},
- title = {The Methodology of Presidential Research},
- year = {1993},
- publisher = {University of Pittsburgh},
- pages = {387--412},
- address = {Pittsburgh},
- editor = {George Edwards, III, John H. Kessel, and Bert
- A. Rockman, eds.},
- note =
- {{http://gking.harvard.edu/files/abs/methpres-abs.shtml}},
- journal = {Researching the Presidency: Vital Questions, New
- Approaches}
-}
-
- at article{KingBruGil93,
- author = {Gary King and John M. Bruce and Michael Gilligan},
- title = {The Science of Political Science Graduate
- Admissions},
- journal = {PS: Political Science and Politics},
- volume = {XXVI},
- year = {1993},
- pages = {772--778},
- month = {December},
- number = {4},
- note = {{http://gking.harvard.edu/files/abs/admis-abs.shtml}}
-}
-
- at article{KinLav93,
- author = {Gary King and Michael Laver},
- title = {On Party Platforms, Mandates, and Government
- Spending},
- journal = {American Political Science Review},
- volume = {87},
- year = {1993},
- pages = {744--750},
- month = {September},
- number = {3},
- note = {{http://gking.harvard.edu/files/abs/hoff-abs.shtml}}
-}
-
- at article{KinWal93,
- author = {Gary King and Daniel J. Walsh},
- title = {Good Research and Bad Research: Extending Zimile's
- Criticism},
- journal = {Early Childhood Research Quarterly},
- volume = {8},
- year = {1993},
- pages = {397--401},
- month = {September},
- number = {3},
- note = {{http://gking.harvard.edu/files/abs/good-abs.shtml}}
-}
-
- at article{King91,
- author = {Gary King},
- title = {'Truth' is Stranger than Prediction, More
- Questionable Than Causal Inference},
- journal = {American Journal of Political Science},
- volume = {35},
- year = {1991},
- pages = {1047--1053},
- month = {November},
- number = {4},
- note = {{http://gking.harvard.edu/files/abs/truth-abs.shtml}}
-}
-
- at article{King91b,
- author = {Gary King},
- title = {Constituency Service and Incumbency Advantage},
- journal = {British Journal of Political Science},
- volume = {21},
- year = {1991},
- pages = {119--128},
- month = {January},
- number = {1},
- note =
- {{http://gking.harvard.edu/files/abs/constit-abs.shtml}}
-}
-
- at article{King91c,
- author = {Gary King},
- title = {On Political Methodology},
- journal = {Political Analysis},
- volume = {2},
- year = {1991},
- pages = {1--30},
- note =
- {{http://gking.harvard.edu/files/abs/polmeth-abs.shtml}}
-}
-
- at article{King91d,
- author = {Gary King},
- title = {Stochastic Variation: A Comment on Lewis-Beck and
- Skalaban's `The R-Square'},
- journal = {Political Analysis},
- volume = {2},
- year = {1991},
- pages = {185--200},
- note = {{http://gking.harvard.edu/files/abs/stoch-abs.shtml}}
-}
-
- at article{King91e,
- author = {Gary King},
- title = {Calculating Standard Errors of Predicted Values
- based on Nonlinear Functional Forms},
- journal = {The Political Methodologist},
- volume = {4},
- year = {1991},
- month = {Fall},
- number = {2}
-}
-
- at article{KinGel91,
- author = {Gary King and Andrew Gelman},
- title = {Systemic Consequences of Incumbency Advantage in the
- U.S. House},
- journal = {American Journal of Political Science},
- volume = 35,
- year = 1991,
- pages = {110--138},
- month = {February},
- number = 1 ,
- note =
- {{http://gking.harvard.edu/files/abs/sysconseq-abs.shtml}}
-}
-
- at article{AnsKin90,
- author = {Stephen Ansolabehere and Gary King},
- title = {Measuring the Consequences of Delegate Selection
- Rules in Presidential Nominations},
- journal = {Journal of Politics},
- volume = {52},
- year = {1990},
- pages = {609--621},
- month = {May},
- number = {2},
- note = {{http://gking.harvard.edu/files/abs/pri-abs.shtml}}
-}
-
- at article{GelKin90,
- author = {Andrew Gelman and Gary King},
- title = {Estimating the Electoral Consequences of Legislative
- Redistricting},
- journal = {Journal of the American Statistical Association},
- volume = {85},
- year = {1990},
- pages = {274--282},
- month = {June},
- number = {410},
- note = {{http://gking.harvard.edu/files/abs/svstat-abs.shtml}}
-}
-
- at article{GelKin90b,
- author = {Andrew Gelman and Gary King},
- title = {Estimating Incumbency Advantage Without Bias},
- journal = {American Journal of Political Science},
- volume = {34},
- year = {1990},
- pages = {1142--1164},
- month = {November},
- number = {4},
- note = {{http://gking.harvard.edu/files/abs/inc-abs.shtml}}
-}
-
- at article{KinAltBur90,
- author = {Gary King and James Alt and Nancy Burns and Michael
- Laver},
- title = {A Unified Model of Cabinet Dissolution in
- Parliamentary Democracies},
- journal = {American Journal of Political Science},
- volume = {34},
- year = {1990},
- pages = {846--871},
- month = {August},
- number = {3},
- note = {{http://gking.harvard.edu/files/abs/coal-abs.shtml}}
-}
-
- at article{King90,
- author = {Gary King},
- title = {Electoral Responsiveness and Partisan Bias in
- Multiparty Democracies},
- journal = {Legislative Studies Quarterly},
- volume = {XV},
- year = {1990},
- pages = {159--181},
- month = {May},
- number = {2},
- note =
- {{http://gking.harvard.edu/files/abs/electresp-abs.shtml}}
-}
-
- at article{GelKin89,
- author = {Andrew Gelman and Gary King},
- title = {Electoral Responsiveness in U.S. Congressional
- Elections, 1946-1986},
- journal = {Proceedings of the Social Statistics Section,
- American Statistical Association},
- year = {1989},
- pages = {208}
-}
-
- at article{King89b,
- author = {Gary King},
- title = {Representation Through Legislative Redistricting: A
- Stochastic Model},
- journal = {American Journal of Political Science},
- volume = {33},
- year = {1989},
- pages = {787--824},
- month = {November},
- number = {4},
- note =
- {{http://gking.harvard.edu/files/abs/repstoch-abs.shtml}}
-}
-
- at article{King89c,
- author = {Gary King},
- title = {Event Count Models for International Relations:
- Generalizations and Applications},
- journal = {International Studies Quarterly},
- volume = {33},
- year = {1989},
- pages = {123--147},
- month = {June},
- number = {2},
- note = {{http://gking.harvard.edu/files/abs/ISQ33-abs.shtml}}
-}
-
- at article{King89d,
- author = {Gary King},
- title = {Variance Specification in Event Count Models: From
- Restrictive Assumptions to a Generalized Estimator},
- journal = {American Journal of Political Science},
- volume = 33,
- year = 1989,
- pages = {762--784},
- month = {August},
- number = 3 ,
- note =
- {{http://gking.harvard.edu/files/abs/varspecec-abs.shtml}}
-}
-
- at article{King89e,
- author = {Gary King},
- title = {A Seemingly Unrelated Poisson Regression Model},
- journal = {Sociological Methods and Research},
- volume = {17},
- year = {1989},
- pages = {235--255},
- month = {February},
- number = {3},
- note = {{http://gking.harvard.edu/files/abs/SMR17-abs.shtml}}
-}
-
- at article{King88,
- author = {Gary King},
- title = {Statistical Models for Political Science Event
- Counts: Bias in Conventional Procedures and Evidence
- for The Exponential Poisson Regression Model},
- journal = {American Journal of Political Science},
- volume = 32,
- year = 1988,
- pages = {838-863},
- month = {August},
- number = 3 ,
- note = {{http://gking.harvard.edu/files/abs/epr-abs.shtml}}
-}
-
- at article{BroKin87,
- author = {Robert X Browning and Gary King},
- title = {Seats, Votes, and Gerrymandering: Measuring Bias and
- Representation in Legislative Redistricting},
- journal = {Law and Policy},
- volume = {9},
- year = {1987},
- pages = {305--322},
- month = {July},
- number = {3},
- note = {{http://gking.harvard.edu/files/abs/LP9-abs.shtml}}
-}
-
- at article{KinBro87,
- author = {Gary King and Robert X Browning},
- title = {Democratic Representation and Partisan Bias in
- Congressional Elections},
- journal = {American Political Science Review},
- volume = {81},
- year = {1987},
- pages = {1252--1273},
- month = {December},
- number = {4},
- note = {{http://gking.harvard.edu/files/abs/sv-abs.shtml}}
-}
-
- at article{King87,
- author = {Gary King},
- title = {Presidential Appointments to the Supreme Court:
- Adding Systematic Explanation to Probabilistic
- Description},
- journal = {American Politics Quarterly},
- volume = {15},
- year = {1987},
- pages = {373--386},
- month = {July},
- number = {3},
- note = {{http://gking.harvard.edu/files/abs/sct-abs.shtml}}
-}
-
- at article{King86,
- author = {Gary King},
- title = {How Not to Lie With Statistics: Avoiding Common
- Mistakes in Quantitative Political Science},
- journal = {American Journal of Political Science},
- volume = {30},
- year = {1986},
- pages = {666--687},
- month = {August},
- number = {3},
- note = {{http://gking.harvard.edu/files/abs/mist-abs.shtml}}
-}
-
- at article{King86b,
- author = {Gary King},
- title = {The Significance of Roll Calls in Voting Bodies: A
- Model and Statistical Estimation},
- journal = {Social Science Research},
- volume = {15},
- year = {1986},
- pages = {135--152},
- month = {June},
- note = {{http://gking.harvard.edu/files/abs/SSR15-abs.shtml}}
-}
-
- at article{King86c,
- author = {Gary King},
- title = {Political Parties and Foreign Policy: A
- Structuralist Approach},
- journal = {Political Psychology},
- volume = {7},
- year = {1986},
- pages = {83--101},
- month = {March},
- number = {1},
- note = {{http://gking.harvard.edu/files/abs/PP7-abs.shtml}}
-}
-
- at article{KinMer86,
- author = {Gary King and Richard Merelman},
- title = {The Development of Political Activists: A Model of
- Early Learning},
- journal = {Social Science Quarterly},
- volume = {67},
- year = {1986},
- pages = {473--490},
- month = {September},
- number = {3},
- note =
- {{http://gking.harvard.edu/files/abs/poliactiv-abs.shtml}}
-}
-
-
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-% Data
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-
- at Article{IacKinPor11b,
- author = {Stefano M. Iacus and Gary King and Giuseppe Porro},
- title = {Replication data for: Causal Inference Without
- Balance Checking: Coarsened Exact Matching},
- journal = { },
- year = 2011,
- note = {http://hdl.handle.net/1902.1/15601 Murray Research
- Archive [Distributor] V1 [Version]}
-}
-
- at article{HopKin09b,
- author = {Daniel Hopkins and Gary King},
- title = {Replication Data for: A Method of Automated
- Nonparametric Content Analysis for Social Science},
- journal = { },
- year = 2009,
- note = {\underline{UNF:3:xlE5stLgKvpeMvxzlLxzEQ==}
- hdl:1902.1/12898 Murray Research Archive [Distributor]}
-}
-
-
- at article{KinGakIma09b,
- Author = {Gary King and Emmanuela Gakidou and Kosuke Imai and
- Jason Lakin and Clayton Nall and Ryan T. Moore and
- Nirmala Ravishankar and Manett Vargas and Martha
- Mar{\'i}a T{\'e}llez-Rojo and Juan Eugenio
- Hern{\'a}ndez {\'A}vila and Mauricio Hern{\'a}ndez
- {\'A}vila and H{\'e}ctor Hern{\'a}ndez Llamas},
- title = {Replication Data for: Public Policy for the Poor? A
- Randomized Ten-Month Evaluation of the Mexican
- Universal Health Insurance Program},
- journal = { },
- year = {2009},
- note = {\underline{hdl:1902.1/11044}
- UNF:3:jeUN9XODtYUp2iUbe8gWZQ== Murray Research
- Archive [Distributor]}
-}
-
- at article{ImaKinNal09c,
- author = {Kosuke Imai and Gary King and Clayton Nall},
- title = {Replication Data for: The Essential Role of Pair-Matching in
- Cluster-Randomized Experiments, with Application to
- the Mexican Universal Health Insurance Evaluation: Rejoinder},
- journal = { },
- year = {2009},
- note = {\underline{hdl:1902.1/12730}
- UNF:3:CKs4T0iVYxP36LQSMgAkuw== Murray Research
- Archive [Distributor]}
-}
-
- at article{ImaKinNal09b,
- author = {Kosuke Imai and Gary King and Clayton Nall},
- title = {Replication Data for: The Essential Role of Pair Matching in
- Cluster-Randomized Experiments, with Application to
- the Mexican Universal Health Insurance Evaluation},
- journal = { },
- year = {2009},
- note = {\underline{hdl:1902.1/11047}
- UNF:3:jeUN9XODtYUp2iUbe8gWZQ== Murray Research
- Archive [Distributor]}
-}
-
- at Article{KinZen08,
- author = {Gary King and Langche Zeng},
- title = {Replication data for: Empirical vs. Theoretical
- Claims about Extreme Counterfactuals: A Response},
- journal = { },
- year = 2008,
- note = {\underline{hdl:1902.1/11903}, Murray Research
- Archive [Distributor]}
-}
-
- at article{GakKin06b,
- author = {Emmanuela Gakidou and Gary King},
- title = {Replication data for: Death by Survey: Estimating
- Adult Mortality without Selection Bias from Sibling
- Survival Data},
- year = 2006,
- note = {{\underline{hdl:1902.1/ZMESWNECZW}
- Murray Research Archive [Distributor]}}
-}
-
- at article{GirKin06,
- author = {Federico Girosi and Gary King},
- title = {Cause of Death Data},
- year = {2006},
- note = {{\underline{hdl:1902.1/UOVMCPSWOL}
- UNF:3:9JU+SmVyHgwRhAKclQ85Cg== Murray Research
- Archive [Distributor]}}
-}
-
- at article{HoImaKin06,
- author = {Daniel E. Ho and Kosuke Imai and Gary King and
- Elizabeth A. Stuart},
- title = {Replication Data Set for: Matching as Nonparametric
- Preprocessing for Reducing Model Dependence in
- Parametric Causal Inference},
- year = 2006,
- note = {{\underline{hdl:1902.1/YVDZEQIYDS}
- Murray Research Archive [distributor]}}
-}
-
- at article{KinAlt06,
- author = {Gary King and James E. Alt and Nancy Burns and
- Michael Laver},
- title = {Replication data for: A Unified Model of Cabinet
- Dissolution in Parliamentary Democracies},
- year = {2006},
- note = {{\underline{hdl:1902.1/RMPXNUSBBS}
- UNF:3:lfKIeFJKgejkOzXEY1i6lw== Murray Research
- Archive [Distributor]}}
-}
-
- at article{KinZen06b,
- author = {Gary King and Langche Zeng},
- title = {Replication Data Set for: When Can History be Our
- Guide? The Pitfalls of Counterfactual Inference},
- year = 2006,
- note = {{\underline{hdl:1902.1/DXRXCFAWPK}
- Murray Research Archive [distributor]}}
-}
-
- at article{KinZen06c,
- author = {Gary King and Langche Zeng},
- title = {Replication data for: Detecting Model Depedence in
- Statistical Inference: A Response},
- year = {2006},
- note = {{\underline{hdl:1902.1/FGSRBXXIYT}
- UNF:3:K4/CgnMYDMV6izc5RVOZTA== Murray Research
- Archive [Distributor]}}
-}
-
- at article{KinZen06d,
- author = {Gary King and Langche Zeng},
- title = {Replication data for: When Can History be Our Guide?
- The Pitfalls of Counterfactual Inference},
- year = {2006},
- note = {{\underline{hdl:1902.1/DXRXCFAWPK}
- UNF:3:DaYlT6QSX9r0D50ye+tXpA== Murray Research
- Archive [Distributor]}}
-}
-
- at article{KinZen06e,
- author = {Gary King and Langche Zeng},
- title = {Replication data for: The Dangers of Extreme
- Counterfactuals },
- year = {2006},
- note = {{\underline{hdl:1902.1/UTVMBVNGMX}
- UNF:3:ytKKNjK+yR8Pq3H0RcV6eg== Murray Research
- Archive [Distributor]}}
-}
-
- at article{EpsHoKin05b,
- author = {Lee Epstein and Daniel E. Ho and Gary King and
- Jeffrey A. Segal},
- title = {Replication data for: The Supreme Court During
- Crisis: How War Affects Only Nonwar Cases},
- year = {2005},
- note = {{\underline{hdl:1902.1/RESUDVYWPE}
- UNF:3:ZmbzFbfqogNM0Gb6CcV52A== Murray Research
- Archive [Distributor]}}
-}
-
- at article{BecKinZen04b,
- author = {Nathaniel Beck and Gary King and Langche Zeng},
- title = {Replication data for: Gelpi and Grynaviski},
- year = {2004},
- note = {{\underline{hdl:1902.1/LAAYCJJGDS}
- UNF:3:N0bEAswAlPPVXCxPOZYyqw== Murray Research
- Archive [Distributor]}}
-}
-
- at article{King03b,
- author = {Gary King},
- title = {10 Million International Dyadic Events},
- year = {2003},
- note = {{\underline{hdl:1902.1/FYXLAWZRIA}
- UNF:3:um06qkr/1tAwpS4roUqAiw== Murray Research
- Archive [Distributor]}}
-}
-
- at article{KinZen01c,
- author = {Gary King and Langche Zeng},
- title = {Replication data for: Explaining Rare Events in
- International Relations},
- year = {2001},
- note = {\underline{hdl:1902.1/OUCBSJKXIC}
- UNF:3:vyct3c8fMCdWOdp03NUhaA== Murray Research
- Archive [Distributor]}
-}
-
- at article{KinZen01d,
- author = {Gary King and Langche Zeng},
- title = {Replication data for: Improving Forecats of State
- Failure},
- year = {2001},
- note = {{\underline{hdl:1902.1/RPQIODIANR}
- UNF:3:CEsbEgPxbxExfYuh2NWwWQ== Murray Research
- Archive [Distributor]}}
-}
-
- at article{BecKinZen00b,
- author = {Nathaniel Beck and Gary King and Langche Zeng},
- title = {Replication data for: Improving Quantitative Studies
- of International Conflict: A Conjecture},
- volume = {2000},
- note = {{\underline{hdl:1902.1/SZKONDGOMF}
- UNF:3:rYRDzT8dCJ/BR7V9u8fObA== Murray Research
- Archive [Distributor]}}
-}
-
- at article{KinTomWit00b,
- author = {Gary King and Michael Tomz and Jason Wittenberg},
- title = {Replication data for: Making the Most of Statistical
- Analyses: Improving Interpretation and Presentation},
- year = {2000},
- note = {{\underline{hdl:1902.1/QTCABXZZRQ}
- UNF:3:1VaLflZ/LfB+AISX+hBm1w== Murray Research
- Archive [Distributor]}}
-}
-
- at article{KatKin99b,
- author = {Jonathan Katz and Gary King},
- title = {Replication data for: A Statistical Model of
- Multiparty Electoral Data},
- year = {1999},
- note = {{\underline{hdl:1902.1/QIGTWZYTLZ}
- UNF:3:gwGcKylle0BKJTGv3Zv4OA== Murray Research
- Archive [Distributor]}}
-}
-
- at article{GelKinBos98b,
- author = {Andrew Gelman and Gary King and John Boscardin},
- title = {Replication data for: Estimating the Probability of
- Events that have Never Occurred: When is your Vote
- Decisive},
- year = {1998},
- note = {{\underline{hdl:1902.1/NOLXXTUHNZ}
- UNF:3:ORDulVH6qEb4lsCyDn5W3A== Murray Research
- Archive [Distributor]}}
-}
-
- at article{King97b,
- author = {Gary King},
- title = {Replication data for: A Solution to the Ecological
- Inference Problem: Reconstructing Individuals
- Behavior from Aggregate Data},
- year = {1997},
- note = {{\underline{hdl:1902.1/LWMMKUTYXS}
- UNF:3:DRWozWd89+vNLO7lY2AHbg== Murray Research
- Archive [Distributor]}}
-}
-
- at article{GelKin94d,
- author = {Andrew Gelman and Gary King},
- title = {Replication data for: Enhancing Democracy Through
- Legislative Redistricting},
- year = {1994},
- note = {{\underline{hdl:1902.1/BNCOWNVERH}
- UNF:3:ZXahi7PBFxLRb46sVKOAuQ== Murray Research
- Archive [Distributor]}}
-}
-
- at article{GelKin94e,
- author = {Andrew Gelman and Gary King},
- title = {Replication data for: Unified Methods of Evaluating
- Electoral Systems and Redistricting Plans: United
- States House of Representatives adn Ohio State
- Legislature},
- year = {1994},
- note = {{\underline{hdl:1902.1/JWFTSFKOBK}
- UNF:3:Fi01DWj4Sx+0ZEOEo4TOXA== Murray Research
- Archive [Distributor]}}
-}
-
- at article{King94,
- author = {Gary King},
- title = {Elections to the United States House of
- Representatives, 1898-1992},
- year = {1994},
- note = {{\underline{hdl:1902.1/TQDSSPRDDZ}
- UNF:3:tD8SznMFjKIxWxOqTQaamQ== Murray Research
- Archive [Distributor]}}
-}
-
- at article{GelKin93b,
- author = {Andrew Gelman and Gary King},
- title = {Replication data for: Why Are American Presidential
- Election Campaign Polls so Variable When Votes are
- so Predictable?},
- year = {1993},
- note = {{\underline{hdl:1902.1/SBBXEUSSCW}
- Murray Research Archive [Distributor]}}
-}
-
- at article{KinLav93b,
- author = {Gary King and Michael Laver},
- title = {Replication data for: On Party Platforms, Mandates,
- and Government Spending},
- year = {1993},
- note = {{\underline{hdl:1902.1/XEHYCJAWQD}
- UNF:3:cwNXuRQ/6Lp72obLkttmGg== Murray Research
- Archive [Distributor]}}
-}
-
- at article{King91e,
- author = {Gary King},
- title = {Replication data for: Constituency Service and
- Incumbency Advantage},
- year = {1991},
- note = {{\underline{hdl:1902.1/JTMXGSZXIZ}
- UNF:3:IE4ZSAs8ZzUK+fRXNbVvGw== Murray Research
- Archive [Distributor]}}
-}
-
- at article{King91f,
- author = {Gary King},
- title = {Replication data for: On Political Methodology},
- year = {1991},
- note = {{\underline{hdl:1902.1/KHTLSQXAEJ}
- Murray Research Archive [Distributor]}}
-}
-
- at article{AnsKin90b,
- author = {Stephen Ansolabehere and Gary King},
- title = {Replication data for: Measuring the Consequences of
- Delegate Selection Rules in Presidential
- Nominations},
- year = {1990},
- note = {{\underline{hdl:1902.1/BUJXCEPXQK}
- UNF:3:OdFPcQcvfO5hc3WJ5ty8vQ== Murray Research
- Archive [Distributor]}}
-}
-
- at article{KinBen86,
- author = {Gary King and Gerald Benjamin},
- title = {Replication data for: The Stability of Partisan
- Identification in the U.S. House of Representatives,
- 1789-1984},
- year = {1986},
- note = {{\underline{hdl:1902.1/HINHTJQYFO}
- Murray Research Archive [Distributor]}}
-}
-
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-% Software
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-
-
- at Article{IacKinPor09b,
- author = {Stefano M. Iacus and Gary King and Giuseppe Porro},
- title = {CEM: Coarsened Exact Matching Software},
- journal = {Journal of Statistical Software},
- volume = 30,
- issue = 9,
- year = 2009,
- note = {{http://gking.harvard.edu/cem}}
-}
-
- at article{WanKinLau07,
- author = {Jonathan Wand and Gary King and Olivia Lau},
- title = {Anchors: Software for Anchoring Vignettes Data},
- journal = {Journal of Statistical Software},
- year = {2007, forthcoming}
-}
-
- at Article{HonKinBLa10,
- author = {James Honaker and Gary King and Matthew Blackwell},
- title = {Amelia II: A Program for Missing Data},
- year = 2010,
- note = {{http://gking.harvard.edu/amelia}}
-}
-
- at article{ImaKinLau06,
- author = {Kosuke Imai and Gary King and Olivia Lau},
- title = {Zelig: Everyone's Statistical Software},
- year = 2006,
- note = {{http://gking.harvard.edu/zelig}}
-}
-
- at article{TomWitKin05,
- author = {Michael Tomz and Jason Wittenberg and Gary King},
- title = {CLARIFY: Software for Interpreting and Presenting
- Statistical Results},
- year = {1998-2005},
- note = {{http://gking.harvard.edu/stats.shtml#clarify}}
-}
-
- at article{HonJosKin98,
- author = {James Honaker and Anne Joseph and Gary King and
- Kenneth Scheve and Naunihal Singh.},
- title = {AMELIA: A Program for Missing Data},
- year = {1998-2002},
- note = {{http://gking.harvard.edu/amelia}}
-}
-
- at article{King98,
- author = {Gary King},
- title = {MAXLIK, a set of Gauss programs, annotated for
- pedagogical purposes, to implement the maximum
- likelihood models in Unifying Political Methodology:
- The Likelihood Theory of Statistical Inference},
- year = {1998},
- note = {{http://gking.harvard.edu/stats.shtml#maxlik}}
-}
-
- at article{King96b,
- author = {Gary King},
- title = {EI: Program for Ecological Inference},
- year = {1996-2003},
- note = {{http://gking.harvard.edu/stats.shtml#ei}}
-}
-
- at article{GelKin92,
- author = {Andrew Gelman and Gary King},
- title = {JudgeIt: A Program for Evaluating Electoral Systems
- and Redistricting Plans},
- year = {1992-2002},
- note = {{http://gking.harvard.edu/stats.shtml#judgeit}}
-}
-
- at article{HoImaKin07a,
- author = {Daniel E. Ho and Kosuke Imai and Gary King and
- Elizabeth A. Stuart},
- title = {MatchIt: Nonparametric Preprocessing for Parametric
- Causal Inference},
- year = {Forthcoming},
- journal = {Journal of Statistical Software},
- note = {{http://gking.harvard.edu/matchit}}
-}
-
- at InCollection{Gelman04,
- author = {Andrew Gelman},
- title = {Treatment Effects in Before-After Data},
- booktitle = {Applied Bayesian Modeling and Causal Inference from
- an Incomplete Data Perspective},
- publisher = {Wiley},
- year = 2004,
- editor = {Andrew Gelman and Xiao-Li Meng},
- chapter = 18,
- address = {London}
-}
-
diff --git a/vignettes/graphics.R b/vignettes/graphics.R
deleted file mode 100644
index 2dc558a..0000000
--- a/vignettes/graphics.R
+++ /dev/null
@@ -1,48 +0,0 @@
-# File to create sample graphics and output for documentation
-
-library(MatchIt)
-library(lattice)
-data(lalonde)
-m.out <- matchit(treat ~ re74+re75+educ+black+hispan+age, data=lalonde, method="nearest")
-
-print(summary(m.out))
-
-ps.options(family = c("Times"), pointsize = 8)
-
-postscript(file="figs/qqplotnn1.eps", horizontal=FALSE, paper="special", width=2.75, height=2.75)
-par(mar=c(2, 2, 2, 2) + 0.1, cex.lab=0.7, cex.axis=0.5,
- mgp=c(1,0.5,0), cex.main=0.8, cex=1, bg="white", mfrow=c(1,2))
-plot(m.out, which.xs=c("re74", "re75", "educ"), interactive=FALSE)
-dev.off()
-
-pdf(file="figs/qqplotnn1.pdf", width=2.75, height=2.75, pointsize=8, family="Times")
-par(mar=c(2, 2, 2, 2) + 0.1, cex.lab=0.7, cex.axis=0.5,
- mgp=c(1,0.5,0), cex.main=0.8, cex=1, bg="white", mfrow=c(1,2))
-plot(m.out, which.xs=c("re74", "re75", "educ"), interactive=FALSE)
-dev.off()
-
-postscript(file="figs/qqplotnn2.eps", horizontal=FALSE, paper="special", width=2.75, height=2.75)
-par(mar=c(2, 2, 2, 2) + 0.1, cex.lab=0.7, cex.axis=0.5,
- mgp=c(1,0.5,0), cex.main=0.8, cex=1, bg="white", mfrow=c(1,2))
-plot(m.out, which.xs=c("black", "hispan", "educ"), interactive=FALSE)
-dev.off()
-
-pdf(file="figs/qqplotnn2.pdf", width=2.75, height=2.75, pointsize=8, family="Times")
-par(mar=c(2, 2, 2, 2) + 0.1, cex.lab=0.7, cex.axis=0.5,
- mgp=c(1,0.5,0), cex.main=0.8, cex=1, bg="white", mfrow=c(1,2))
-plot(m.out, which.xs=c("black", "hispan", "educ"), interactive=FALSE)
-dev.off()
-
-postscript(file="figs/jitterplotnn.eps", horizontal=FALSE, paper="special", width=5.5, height=3.5)
-par(mar=c(2, 2, 2, 2) + 0.1, cex.lab=0.7, cex.axis=0.5,
- mgp=c(1,0.5,0), cex.main=0.8, cex=1, bg="white")
-plot(m.out, type="jitter", interactive=FALSE)
-dev.off()
-
-pdf(file="figs/jitterplotnn.pdf", width=5.5, height=3.5, pointsize=8, family="Times")
-par(mar=c(2, 2, 2, 2) + 0.1, cex.lab=0.7, cex.axis=0.5,
- mgp=c(1,0.5,0), cex.main=0.8, cex=1, bg="white")
-plot(m.out, type="jitter", interactive=FALSE)
-dev.off()
-
-
diff --git a/vignettes/html.sty b/vignettes/html.sty
deleted file mode 100644
index 191bb19..0000000
--- a/vignettes/html.sty
+++ /dev/null
@@ -1,360 +0,0 @@
-% LaTeX2HTML Version 95.1 : html.sty
-%
-% WARNING: This file requires LaTeX2e. A LaTeX 2.09 version
-% is also provided, but with restricted functionality.
-%
-% This file contains definitions of LaTeX commands which are
-% processed in a special way by the translator.
-% For example, there are commands for embedding external hypertext links,
-% for cross-references between documents or for including
-% raw HTML.
-% This file includes the comments.sty file v2.0 by Victor Eijkhout
-% In most cases these commands do nothing when processed by LaTeX.
-
-% Modifications:
-%
-% nd = Nikos Drakos <nikos at cbl.leeds.ac.uk>
-% jz = Jelle van Zeijl <jvzeijl at isou17.estec.esa.nl>
-% hs = Herb Swan <dprhws at edp.Arco.com>
-
-% hs 31-JAN-96 - Added support for document segmentation
-% hs 10-OCT-95 - Added \htmlrule command
-% jz 22-APR-94 - Added support for htmlref
-% nd - Created
-%%%%MG added
-\NeedsTeXFormat{LaTeX2e}
-\ProvidesPackage{html}
- [1996/02/01 v1.0 hypertext commands for latex2html (nd, hs)]
-%%%%MG
-% Exit if the style file is already loaded
-% (suggested by Lee Shombert <las at potomac.wash.inmet.com>
-\ifx \htmlstyloaded\relax \endinput\else\let\htmlstyloaded\relax\fi
-
-%%% LINKS TO EXTERNAL DOCUMENTS
-%
-% This can be used to provide links to arbitrary documents.
-% The first argumment should be the text that is going to be
-% highlighted and the second argument a URL.
-% The hyperlink will appear as a hyperlink in the HTML
-% document and as a footnote in the dvi or ps files.
-%
-\newcommand{\htmladdnormallinkfoot}[2]{#1\footnote{#2}}
-
-% This is an alternative definition of the command above which
-% will ignore the URL in the dvi or ps files.
-\newcommand{\htmladdnormallink}[2]{#1}
-
-% This command takes as argument a URL pointing to an image.
-% The image will be embedded in the HTML document but will
-% be ignored in the dvi and ps files.
-%
-\newcommand{\htmladdimg}[1]{}
-
-%%% CROSS-REFERENCES BETWEEN (LOCAL OR REMOTE) DOCUMENTS
-%
-% This can be used to refer to symbolic labels in other Latex
-% documents that have already been processed by the translator.
-% The arguments should be:
-% #1 : the URL to the directory containing the external document
-% #2 : the path to the labels.pl file of the external document.
-% If the external document lives on a remote machine then labels.pl
-% must be copied on the local machine.
-%
-%e.g. \externallabels{http://cbl.leeds.ac.uk/nikos/WWW/doc/tex2html/latex2html}
-% {/usr/cblelca/nikos/tmp/labels.pl}
-% The arguments are ignored in the dvi and ps files.
-%
-\newcommand{\externallabels}[2]{}
-
-%
-% This complements the \externallabels command above. The argument
-% should be a label defined in another latex document and will be
-% ignored in the dvi and ps files.
-%
-\newcommand{\externalref}[1]{}
-
-% This command adds a horizontal rule and is valid even within
-% a figure caption.
-%
-\newcommand{\htmlrule}{}
-
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-%
-% The following commands pertain to document segmentation, and
-% were added by Herbert Swan <dprhws at edp.Arco.com> (with help from
-% Michel Goossens <goossens at cern.ch>):
-%
-%
-% This command inputs internal latex2html tables so that large
-% documents can to partitioned into smaller (more manageable)
-% segments.
-%
-\newcommand{\internal}[2][internals]{}
-
-%
-% Define a dummy stub \htmlhead{}. This command causes latex2html
-% to define the title of the start of a new segment. It is not
-% normally placed in the user's document. Rather, it is passed to
-% latex2html via a .ptr file written by \segment.
-%
-\newcommand{\htmlhead}[2]{}
-
-%
-% The dummy command \endpreamble is needed by latex2html to
-% mark the end of the preamble in document segments that do
-% not contain a \begin{document}
-%
-\newcommand{\startdocument}{}
-
-%
-% Allocate a new set of section counters, which will get incremented
-% for "*" forms of sectioning commands, and for a few miscellaneous
-% commands.
-%
-
-\newcounter{lpart}
-\newcounter{lchapter}[part]
-\ifx\chapter\undefined\newcounter{lsection}[part]\else\newcounter{lsection}[chapter]\fi
-\newcounter{lsubsection}[section]
-\newcounter{lsubsubsection}[subsection]
-\newcounter{lparagraph}[subsubsection]
-\newcounter{lsubparagraph}[paragraph]
-\newcounter{lsubsubparagraph}[subparagraph]
-\newcounter{lequation}
-%
-% Redefine "*" forms of sectioning commands to increment their
-% respective counters.
-%
-\let\Hpart=\part
-\let\Hchapter=\chapter
-\let\Hsection=\section
-\let\Hsubsection=\subsection
-\let\Hsubsubsection=\subsubsection
-\let\Hparagraph=\paragraph
-\let\Hsubparagraph=\subparagraph
-\let\Hsubsubparagraph=\subsubparagraph
-
-%
-% The following definitions are specific to LaTeX2e:
-% (They must be commented out for LaTeX 2.09)
-%
-\def\part{\@ifstar{\stepcounter{lpart}\Hpart*}{\Hpart}}
-\def\chapter{\@ifstar{\stepcounter{lchapter}\Hchapter*}{\Hchapter}}
-\def\section{\@ifstar{\stepcounter{lsection}\Hsection*}{\Hsection}}
-\def\subsection{\@ifstar{\stepcounter{lsubsection}\Hsubsection*}{\Hsubsection}}
-\def\subsubsection{\@ifstar{\stepcounter{lsubsubsection}\Hsubsubsection*}{\Hsubsubsection}}
-\def\paragraph{\@ifstar{\stepcounter{lparagraph}\Hparagraph*}{\Hparagraph}}
-\def\subparagraph{\@ifstar{\stepcounter{lsubparagraph}\Hsubparagraph*}{\Hsubparagraph}}
-\def\subsubparagraph{\@ifstar{\stepcounter{lsubsubparagraph}\Hsubsubparagraph*}{\Hsubsubparagraph}}
-%
-% Define a helper macro to dump a single \secounter command to a file.
-%
-\newcommand{\DumpPtr}[2]{%
-\count255=\arabic{#1} \advance\count255 by \arabic{#2}
-\immediate\write\ptrfile{%
-\noexpand\setcounter{#1}{\number\count255}}}
-
-%
-% Define a helper macro to dump all counters to the file.
-% The value for each counter will be the sum of the l-counter
-% actual LaTeX section counter.
-% Also dump an \htmlhead{section-command}{section title} command
-% to the file.
-%
-
-\def\DumpCounters#1#2#3{\newwrite\ptrfile
-\immediate\openout\ptrfile = #1.ptr
-\DumpPtr{part}{lpart}
-\ifx\Hchapter\undefined\relax\else\DumpPtr{chapter}{lchapter}\fi
-\DumpPtr{section}{lsection}
-\DumpPtr{subsection}{lsubsection}
-\DumpPtr{subsubsection}{lsubsubsection}
-\DumpPtr{paragraph}{lparagraph}
-\DumpPtr{subparagraph}{lsubparagraph}
-\DumpPtr{equation}{lequation}
-\immediate\write\ptrfile{\noexpand\htmlhead{#2}{#3}}
-\immediate\closeout\ptrfile}
-
-%
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-\def\segment{\@ifstar{\@@htmls}{\@@html}}
-\def\@@htmls#1#2#3{\csname #2\endcsname* {#3}%
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-\def\@@html#1#2#3{\csname #2\endcsname {#3}%
- \DumpCounters{#1}{#2}{#3}\input{#1}}
-%%%%MG
-
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-% Comment.sty version 2.0, 19 June 1992
-% selectively in/exclude pieces of text: the user can define new
-% comment versions, and each is controlled separately.
-% This style can be used with plain TeX or LaTeX, and probably
-% most other packages too.
-%
-% Examples of use in LaTeX and TeX follow \endinput
-%
-% Author
-% Victor Eijkhout
-% Department of Computer Science
-% University Tennessee at Knoxville
-% 104 Ayres Hall
-% Knoxville, TN 37996
-% USA
-%
-% eijkhout at cs.utk.edu
-%
-% Usage: all text included in between
-% \comment ... \endcomment
-% or \begin{comment} ... \end{comment}
-% is discarded. The closing command should appear on a line
-% of its own. No starting spaces, nothing after it.
-% This environment should work with arbitrary amounts
-% of comment.
-%
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-% \excludecoment{versionb}
-%
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-% \versiona ... \endversiona
-% or \begin{versiona} ... \end{versiona}
-% with the closing command again on a line of its own.
-%
-% Basic approach:
-% to comment something out, scoop up every line in verbatim mode
-% as macro argument, then throw it away.
-% For inclusions, both the opening and closing comands
-% are defined as noop
-%
-% Changed \next to \html at next to prevent clashes with other sty files
-% (mike at emn.fr)
-% Changed \html at next to \htmlnext so the \makeatletter and
-% \makeatother commands could be removed (they were causing other
-% style files - changebar.sty - to crash) (nikos at cbl.leeds.ac.uk)
-% Changed \htmlnext back to \html at next...
-
-\makeatletter
-\def\makeinnocent#1{\catcode`#1=12 }
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-% Shorter version
-\newcommand{\html}[1]{}
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-
-%%% LaTeX ONLY
-% Enclose LaTeX constructs which will only appear in the
-% DVI output and will be ignored by latex2html with
-%\begin{latexonly} and \end{latexonly}
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-% Shorter version
-\newcommand{\latex}[1]{#1}
-
-%%% HYPERREF
-% Suggested by Eric M. Carol <eric at ca.utoronto.utcc.enfm>
-% Similar to \ref but accepts conditional text.
-% The first argument is HTML text which will become ``hyperized''
-% (underlined).
-% The second and third arguments are text which will appear only in the paper
-% version (DVI file), enclosing the fourth argument which is a reference to a label.
-%
-%e.g. \hyperref{using the tracer}{using the tracer (see Section}{)}{trace}
-% where there is a corresponding \label{trace}
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-\newcommand{\hyperref}[4]{#2\ref{#4}#3}
-
-%%% HTMLREF
-% Reference in HTML version only.
-% Mix between \htmladdnormallink and \hyperref.
-% First arg is text for in both versions, second is label for use in HTML
-% version.
-\newcommand{\htmlref}[2]{#1}
-
-%%% HTMLIMAGE
-% This command can be used inside any environment that is converted
-% into an inlined image (eg a "figure" environment) in order to change
-% the way the image will be translated. The argument of \htmlimage
-% is really a string of options separated by commas ie
-% [scale=<scale factor>],[external],[thumbnail=<reduction factor>
-% The scale option allows control over the size of the final image.
-% The ``external'' option will cause the image not to be inlined
-% (images are inlined by default). External images will be accessible
-% via a hypertext link.
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-% placed in the caption. The size of the thumbnail depends on the
-% reduction factor. The use of the ``thumbnail'' option implies
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-%
-% Example:
-% \htmlimage{scale=1.5,external,thumbnail=0.2}
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-% placed in the final document, pointing to an external image 1.5
-% times bigger than the original.
-%
-\newcommand{\htmlimage}[1]{}
-
-%%% HTMLADDTONAVIGATION
-% This command appends its argument to the buttons in the navigation
-% panel. It is ignored by LaTeX.
-%
-% Example:
-% \htmladdtonavigation{\htmladdnormallink
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-% {http://server/path}}
-\newcommand{\htmladdtonavigation}[1]{}
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\ No newline at end of file
diff --git a/vignettes/index.shtml b/vignettes/index.shtml
deleted file mode 100755
index 8d2615e..0000000
--- a/vignettes/index.shtml
+++ /dev/null
@@ -1,72 +0,0 @@
-<html>
-<head>
-<title>MatchIt Software Website</title>
-<script language='Javascript' src='/gking.js'></script></HEAD>
-
-<BODY><script language="Javascript">displayHeader('MatchIt: Nonparametric Preprocessing for Parametric Causal Inference')</script>
-
-<p><a href="http://people.iq.harvard.edu/~dho/" target="gkingext">Daniel Ho</a>,
-<a href="http://www.princeton.edu/~kimai/" target="gkingext">Kosuke Imai</a>,
-<a href="http://GKing.Harvard.edu">Gary King</a>,
-<a href="http://people.iq.harvard.edu/~estuart/" target="gkingext">Elizabeth Stuart</a>
-
-<p>"At MatchIt, we don't make parametric models, we make parametric models
-work better."
-
-<!-- rbuild: replace 'Version:' '</b>' version -->
-<p><b>Version:2.2-3</b>
-
- <table width="90%" border="0" cellpadding="10">
- <tr>
- <td valign='top'><img src="face_off.jpg" width="200"></td>
-
- <td valign="top"><br>MatchIt implements the suggestions of <a
- href="http://gking.harvard.edu/files/abs/matchp-abs.shtml">Ho, Imai, King, and Stuart
- (2007)</a> for improving parametric statistical
- models by
- preprocessing data with nonparametric matching methods. MatchIt
- implements a wide range of sophisticated matching methods,
- making it possible to greatly reduce the dependence of causal
- inferences on hard-to-justify, but commonly made, statistical
- modeling assumptions. The software also easily fits into
- existing research practices since, after preprocessing data with
- MatchIt, researchers can use whatever parametric model they
- would have used without MatchIt, but produce inferences with
- substantially more robustness and less sensitivity to modeling
- assumptions. MatchIt is an <a
- href="http://www.r-project.org" target="gkingext">R</a> program, and also works
- seamlessly with <a href="http://gking.harvard.edu/zelig/">Zelig</a>.
-
-<ul>
- <li>Documentation: <!-- <a href="http://gking.harvard.edu/matchit/docs/">HTML</a> or --> <a
-href="http://gking.harvard.edu/matchit/docs/matchit.pdf">PDF</a>
- <!-- <li><a
-href="http://gking.harvard.edu/matchit/docs/Installing_M_SMALL_ATC.html">Installation
-and Downloads</a> -->
-
-<li>All questions, bugs and requests: MatchIt Mailing List: <a
-href="http://lists.hmdc.harvard.edu/index.cgi?info=matchit"
-target="gkingext">[Un]Subscribe</a>, or <a
-href="http://lists.hmdc.harvard.edu/lists/matchit/"
-target="gkingext">Browse/Search Archives</a>
-
-</ul>
-
-We're pleased to report that the <a
-href="http://gking.harvard.edu/files/abs/matchp-abs.shtml">article</a> on which MatchIt is
-based won the <em>Warren Miller Prize</em> for the best paper in
-<em>Political Analysis</em> that year and, separately, has been named a
- <em>Fast Breaking Paper</em> by Thomson Reuters' ScienceWatch, for
- being the article with the largest
- percentage increase in citations among those in the top 1% of
- total citations across the social sciences in the last two years.
- (You may be interested in this interview: <a
- href="http://sciencewatch.com/dr/fbp/2008/08octfbp/08octfbpHoET/">HTML</a> |
- <a href="http://gking.harvard.edu/files/fbp08.pdf">PDF</a>)
-
-</td>
- </tr>
- </table>
-
-<script language="Javascript">displayFooter()</script></BODY>
-</html>
diff --git a/vignettes/intro.tex b/vignettes/intro.tex
deleted file mode 100644
index 572372b..0000000
--- a/vignettes/intro.tex
+++ /dev/null
@@ -1,84 +0,0 @@
-
-\section{What \MatchIt\ Does}
-
-\MatchIt\ implements the suggestions of \citet*{HoImaKin07} for
-improving parametric statistical models and reducing model dependence
-by preprocessing data with semi-parametric and non-parametric matching
-methods. After appropriately preprocessing with \MatchIt, researchers
-can use whatever parametric model and software they would have used
-without \MatchIt, without other modification, and produce inferences
-that are more robust and less sensitive to modeling assumptions. (In
-addition, you may wish to use Zelig
-(\hlink{\url{http://gking.harvard.edu/zelig/}}{http://gking.harvard.edu/zelig/};
-\citealt{ImaKinLau06} for subsequent parametric analyses, as it is
-designed to be convenient in analyzing \MatchIt\ data sets.)
-\MatchIt\ reduces the dependence of causal inferences on commonly
-made, but hard-to-justify, statistical modeling assumptions via the
-largest range of sophisticated matching methods of any software we
-know of. The program includes most existing approaches to matching
-and even enables users to access methods implemented in other programs
-through its single, unified, and easy-to-use interface. In addition,
-we have written \MatchIt\ so that adding new matching methods to the
-software is as easy for anyone with the inclination as it is for us.
-
-\section{Software Requirements}
-\label{sec:require}
-
-\MatchIt\ works in conjunction with the R programming language and
-statistical software, and will run on any platform where R is
-installed (Windows, Unix, or Mac OS X). R is available free for
-download at the Comprehensive R Archive Network (CRAN) at
-\hlink{http://cran.r-project.org/}{http://cran.r-project.org/}.
-\MatchIt\ has been tested on the most recent version of R. A good way
-to learn R, if you don't know it already, is to learn Zelig (available
-at
-\hlink{http://gking.harvard.edu/zelig}{http://gking.harvard.edu/zelig})
-which includes a self-contained introduction to R and can be used to
-analyze the matched data after running \MatchIt.
-
-\section{Installing \MatchIt}
-\label{sec:install}
-
-To install \MatchIt\ for all platforms, type at the R command prompt,
-\begin{verbatim}
-> install.packages("MatchIt")
-\end{verbatim}
-and \MatchIt\ will install itself onto your system automatically.
-(During the installation process you may either decide to keep or
-discard the installation files, which will not affect the way
-\MatchIt\ runs.)
-
-\section{Loading \MatchIt} \label{sec:load}
-
-You need to install \MatchIt\ only once, but you must load it prior to
-each use. You can do this at the R prompt:
-\begin{verbatim}
-> library(MatchIt)
-\end{verbatim}
-
-Alternatively, you can specify R to load \MatchIt\ automatically at
-launch by editing the {\tt Rprofile} file located in the R program
-subdirectory, e.g. \texttt{C:/R/rw2011/etc/}, for Windows systems or
-the {\tt .Rprofile} file located in the home directory for Unix/Linux
-and Mac OS X systems, and adding this line:
-\begin{verbatim}
-options(defaultPackages = c(getOption("defaultPackages"), "MatchIt"))
-\end{verbatim}
-For this change to take effect, you need to restart R.
-
-\section{Updating \MatchIt}
-
-We recommend that you periodically update \MatchIt\ at the R prompt by typing:
-\begin{verbatim}
-> update.packages()
-> library(MatchIt)
-\end{verbatim}
-which will update all the libraries including \MatchIt\ and load the
-new version of \MatchIt.
-
-
-%%% Local Variables:
-%%% mode: pdflatex
-%%% TeX-master: "matchit"
-%%% TeX-master: t
-%%% End:
diff --git a/vignettes/makematchH b/vignettes/makematchH
deleted file mode 100755
index 798c0e2..0000000
--- a/vignettes/makematchH
+++ /dev/null
@@ -1,5 +0,0 @@
-#!/bin/tcsh
-latex matchit
-bibtex matchit
-latex matchit
-latex matchit
diff --git a/vignettes/matchit.pdf b/vignettes/matchit.pdf
deleted file mode 100644
index 4449d3e..0000000
Binary files a/vignettes/matchit.pdf and /dev/null differ
diff --git a/vignettes/matchit.pdf.asis b/vignettes/matchit.pdf.asis
new file mode 100644
index 0000000..0499143
--- /dev/null
+++ b/vignettes/matchit.pdf.asis
@@ -0,0 +1,2 @@
+%\VignetteIndexEntry{MatchIt: Nonparametric Preprocessing for Parametric Causal Inference}
+%\VignetteEngine{R.rsp::asis}
diff --git a/vignettes/matchit.tex b/vignettes/matchit.tex
deleted file mode 100644
index 0483531..0000000
--- a/vignettes/matchit.tex
+++ /dev/null
@@ -1,209 +0,0 @@
-\documentclass[oneside,letterpaper,12pt]{book}
-\usepackage{bibentry}
-\usepackage{graphicx}
-\usepackage{natbib}
-\usepackage[reqno]{amsmath}
-\usepackage{amssymb}
-\usepackage{verbatim}
-\usepackage{epsf}
-\usepackage{url}
-\usepackage{html}
-\usepackage{dcolumn}
-\usepackage{fullpage}
-\bibpunct{(}{)}{;}{a}{}{,}
-\newcolumntype{.}{D{.}{.}{-1}}
-\newcolumntype{d}[1]{D{.}{.}{#1}}
-%\pagestyle{myheadings}
-\htmladdtonavigation{
- \htmladdnormallink{%
- \htmladdimg{http://gking.harvard.edu/pics/home.gif}}
- {http://gking.harvard.edu/}}
-\newcommand{\hlink}{\htmladdnormallink}
-
-%\bodytext{ BACKGROUND="http://gking.harvard.edu/pics/temple.jpg"}
-\setcounter{tocdepth}{3}
-\setcounter{secnumdepth}{4}
-
-\newcommand{\MatchIt}{\textsc{MatchIt}}
-
-\title{\MatchIt: Nonparametric Preprocessing for Parametric Causal
- Inference\thanks{We thank Olivia Lau for helpful suggestions about
- incorporating \MatchIt\, into Zelig.}}
-
-\author{Daniel E. Ho,\thanks{Assistant Professor of Law
-\& Robert E.\ Paradise Faculty Scholar, Stanford Law
- School (559 Nathan Abbott Way, Stanford CA 94305;
- \texttt{http://dho.stanford.edu}, \texttt{dho at law.stanford.edu},
- (650) 723-9560).} \and %
- Kosuke Imai,\thanks{Assistant Professor, Department of Politics,
- Princeton University (Corwin Hall 041, Department of Politics,
- Princeton University, Princeton NJ 08544, USA;
- \texttt{http://imai.princeton.edu},
- \texttt{kimai at Princeton.Edu}).} \and %
- Gary King,\thanks{David Florence Professor of Government, Harvard
- University (Institute for Quantitative Social Science, 1737
- Cambridge Street, Harvard University, Cambridge MA 02138;
- \texttt{http://GKing.Harvard.Edu}, \texttt{King at Harvard.Edu},
- (617) 495-2027).} \and %
-Elizabeth A. Stuart\thanks{Assistant Professor, Departments of Mental
-Health and Biostatistics, Johns Hopkins Bloomberg School of Public Health
-(624 N Broadway, Room 804, Baltimore, MD 21205;
- \texttt{http://www.biostat.jhsph.edu/$\sim$estuart},
- \texttt{estuart at jhsph.edu}).}}
-
-%\makeindex
-
-\begin{document}
-\maketitle
-
-\begin{rawhtml}
- <p> [Also available is a downloadable <a
- href="matchit.pdf">PDF</a> version of this entire
- document]
-\end{rawhtml}
-
-\tableofcontents
-
-\nobibliography*
-
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-\clearpage
-
-\chapter{Introduction}
-\input{intro}
-
-
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-
-\chapter{Statistical Overview}
-\input{overview}
-
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-
-\chapter{User's Guide to \MatchIt}
-\label{methods}
-
-\input{preprocess}
-\input{balance}
-\input{matchit2zelig}
-
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-
-\chapter{Reference Manual}
-\label{chap:reference}
-
-\section{\texttt{matchit()}: Implementation of Matching Methods}
-\label{sec:matchit}
-Use \texttt{matchit()} to implement a variety of matching procedures
-including exact matching, nearest neighbor matching,
-subclassification, optimal matching, genetic matching, and full
-matching. The output of {\tt matchit()} can be analyzed via any
-standard R package, by exporting the data for use in another program,
-or most simply via \hlink{Zelig}{http://gking.harvard.edu/zelig} in R.
-
-\input{matchitref}
-\input{summaryref}
-\input{plotref}
-\input{mdataref}
-\input{faq}
-
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-
-
-\chapter{What's New?}
-
-\begin{itemize}
-\item \textbf{2.4-20} (October 24, 2011): bug fix for GAM models (thanks to Felix Thoemmes)
-\item \textbf{2.4-18} (April 26, 2011): JSS version, no change in code.
-\item \textbf{2.4-17} (April 2, 2011): a minor documentation fix.
-\item \textbf{2.4-16} (January 8, 2011): a bug fix for user defined distance.
-\item \textbf{2.4-15} (December 11, 2010): a bug fix in the
- mahalanobis matching.
-\item \textbf{2.4-14} (August 12, 2010): a bug fix in {\tt
- match.data()} so that it can be called within a function (thanks
- to Ajay Shah, George Baah, and Ben Dominique); \MatchIt now does not
- specify digits for printing (thanks to Chris Hane); A summary table
- of matched data is now stored in the output (thanks to George Baah)
-\item \textbf{2.4-11} (June 25, 2009): More flexible inputs in
- plotting.
-\item \textbf{2.4-10} (February 2, 2009): Minor documentation fixes
-\item \textbf{2.4-8,2.4-9} (January 29, 2009): Minor documentation fixes
-\item \textbf{2.4-7} (August 4, 2008): Fixed minor bug in subclassification
-(thanks to Ben Domingue)
-\item \textbf{2.4-6} (July 21, 2008): Improved summary object for
- exact matching (thanks to Andrew Stokes)
-\item \textbf{2.4-5} (July 20, 2008): Fixed a minor bug.
-\item \textbf{2.4-4} (July 18, 2008): Fixed another bug with regard to the discard option (thanks to Ben Dominique).
-\item \textbf{2.4-3} (July 18, 2008): Fixed a bug in full matching
- regarding the discard option (thanks to Ben Dominique). Some updates
- of documentation regarding coarsened exact matching (2.4-1 and
- 2.4-2).
-\item \textbf{2.4} (June 12, 2008): Included coarsened exact matching;
- documentation bug fixes (thanks to Will Lowe)
-\item \textbf{2.3-1} (October 11, 2007): Stable release for R
- 2.6. Documentation improved. Some minor bug fixes and improvements.
-\item \textbf{2.2-14} (September 2, 2007): Stable release for R 2.5.
- Documentation improved for full matching. (Thanks to Langche Zeng)
-\item \textbf{2.2-13} (April 10, 2007): Stable release for R
- 2.4. Additional fix to package dependencies. Bug fix for summary().
-\item \textbf{2.2-12} (April 6, 2007): Stable release for R 2.4. Fix
- to package dependencies.
-\item \textbf{2.2-11} (July 13, 2006): Stable release for R 2.3.
- Fix to ensure summary() command works with character variables in dataframe (thanks to Daniel Gerlanc).
-\item \textbf{2.2-10} (May 9, 2006): Stable release for R 2.3.
- A bug fix in {\tt demo(analysis)} (thanks to Julia Gray).
-\item \textbf{2.2-9} (May 3, 2006): Stable release for R 2.3.
- A minor change to DESCRIPTION file.
-\item \textbf{2.2-8} (May 1, 2006): Stable release for R 2.3.
- Removed dependency on Zelig (thanks to Dave Kane).
-\item \textbf{2.2-7} (April 11, 2006): Stable release for R 2.2.
- Error message for missing values in the data frame added
- (thanks to Olivia Lau).
-\item \textbf{2.2-6} (April 4, 2006): Stable release for R 2.2.
- Bug fixes related to {\tt reestimate} in {\tt matchit()} and {\tt
- match.data()} (thanks to Ani Ruhil and Claire Aussems).
-\item \textbf{2.2-5} (December 7, 2005): Stable release for R 2.2.
- Changed URL of {\tt WhatIf} to CRAN.
-\item \textbf{2.2-4} (December 3, 2005): Stable release for R 2.2.
- User's own distance measure can be used with \MatchIt\, (thanks to
- Nelson Lim).
-\item \textbf{2.2-3} (November 18, 2005): Stable release for R 2.2.
- standardize option added to full matching and subclass (thanks to
- Jeronimo Cortina).
-\item \textbf{2.2-2} (November 9, 2005): Stable release for R 2.2.
- {\tt optmatch} package now on CRAN. Changed URL for that package.
-\item \textbf{2.2-1} (November 1, 2005): Stable release for R 2.2.
- balance measures based on empirical CDF are added as a new option
- {\tt standardize} in {\tt summary()}.
-\item \textbf{2.1-4} (October 14, 2005): Stable release for R 2.2.
- strictly empirical (no interpolation) quantile-quantile functions
- and plots are used.
-\item \textbf{2.1-3} (September 27, 2005): Stable release for R 2.1.
- automated the installation of optional packages. fixed a coding
- error in {\tt summary()}, the documentation edited.
-\item \textbf{2.1-2} (September 27, 2005): Stable release for R 2.1.
- minor changes to file names, the option {\tt "whichxs"} added to the
- {\tt plot()}, major editing of the documentation.
-\item \textbf{2.1-1} (September 16, 2005): Stable release for R
- 2.1. Genetic matching added.
-\item \textbf{2.0-1} (August 29, 2005): Stable release for R 2.1.
- Major revisions including some syntax changes. Statistical tests are
- no longer used for balance checking, which are now based on the
- empirical covariate distributions (e.g., quantile-quantile plot).
-\item \textbf{1.0-2} (August 10, 2005): Stable release for R
- 2.1. Minor bug fixes (Thanks to Bart Bonikowski).
-\item \textbf{1.0-1} (January 3, 2005): Stable release for R 2.0. The
- first official version of \MatchIt
-\end{itemize}
-
-
-
-\clearpage
-
-\bibliographystyle{asa}
-\bibliography{gk,gkpubs}
-
-\end{document}
-
diff --git a/vignettes/matchit2zelig.tex b/vignettes/matchit2zelig.tex
deleted file mode 100644
index 011e7b2..0000000
--- a/vignettes/matchit2zelig.tex
+++ /dev/null
@@ -1,285 +0,0 @@
-\section{Conducting Analyses after Matching}
-\label{sec:analysis}
-
-Any software package may be used for parametric analysis following
-\MatchIt. This includes any of the relevant R packages, or other
-statistical software by exporting the resulting matched data sets
-using R commands such as {\tt write.csv()} and {\tt write.table()} for
-ASCII files or {\tt write.dta()} in the {\tt foreign} package for a
-STATA binary file.
-
-When variable numbers of treated and control units have been matched
-to each other (e.g., through exact matching, full matching, or k:1
-matching with replacement), the weights created by MatchIt should be
-used (e.g., in a weighted regression) to ensure that the matched
-treated and control groups are weighted up to be similar. Users
-should also remember that the weights created by MatchIt estimate the
-average treatment effect on the treated, with the control units
-weighted to resemble the treated units. See below for more detail on
-the weights. With subclassification, estimates should be obtained
-within each subclass and then aggregated across subclasses. When it
-is not possible to calculate an effect within each subclass, again the
-weights can be used to weight the matched units.
-
-In this section, we show how to use
-\hlink{Zelig}{http://gking.harvard.edu/zelig/} with \MatchIt. Zelig
-\citep{ImaKinLau06} is an R package that implements a large variety of
-statistical models (using numerous existing R packages) with a single
-easy-to-use interface, gives easily interpretable results by
-simulating quantities of interest, provides numerical and graphical
-summaries, and is easily extensible to include new methods.
-
-\subsection{Quick Overview}
-
-The general syntax is as follows. First, we use \texttt{match.data()}
-to create the matched data from the \MatchIt\ output object
-(\texttt{m.out}) by excluding unmatched units from the original data,
-and including information produced by the particular matching
-procedure (i.e., primarily a new data set, but also information that
-may result such as weights, subclasses, or the distance measure).
-\begin{verbatim}
-> m.data <- match.data(m.out)
-\end{verbatim}
-where {\tt m.data} is the resulting matched data. Zelig analyses all
-use three commands --- \texttt{zelig}, \texttt{setx}, and
-\texttt{sim}. For example, the basic statistical analysis is
-performed first:
-\begin{verbatim}
-> z.out <- zelig(Y ~ treat + x1 + x2, model = mymodel, data = m.data)
-\end{verbatim}
-where {\tt Y} is the outcome variable, {\tt mymodel} is the selected
-model, and {\tt z.out} is the output object from {\tt zelig}. This
-output object includes estimated coefficients, standard errors, and
-other typical outputs from your chosen statistical model. Its
-contents can be examined via \texttt{summary(z.out)} or
-\texttt{plot(z.out)}, but the idea of Zelig is that these statistical
-results are typically only intermediate quantities needed to compute
-your ultimate quantities of interest, which in the case of matching
-are usually causal inferences. To get these causal quantities, we use
-Zelig's other two commands. Thus, we can set the explanatory
-variables at their means (the default) and change the treatment
-variable from a 0 to a 1:
-\begin{verbatim}
-> x.out <- setx(z.out, treat=0)
-> x1.out <- setx(z.out, treat=1)
-\end{verbatim}
-and finally compute the resulting estimates of the causal effects and
-examine a summary:
-\begin{verbatim}
-> s.out <- sim(z.out, x = x.out, x1 = x1.out)
-> summary(s.out)
-\end{verbatim}
-
-\subsection{Examples}
-
-We now give four examples using the Lalonde data. They are meant to
-be read sequentially. You can run these example commands by typing
-{\tt demo(analysis)}. Although we use the linear least squares model
-in these examples, a wide range of other models are available in Zelig
-(for the list of supported models, see
-\hlink{\url{http://gking.harvard.edu/zelig/docs/Models_Zelig_Can.html}}
-{http://gking.harvard.edu/zelig/docs/Models_Zelig_Can.html}.
-
-To load the Zelig package after installing it, type
-\begin{verbatim}
-> library(Zelig)
-\end{verbatim}
-
-\begin{description}
-\item[Model-Based Estimates] In our first example, we conduct a
- standard parametric analysis and compute quantities of interest in
- the most common way. We begin with nearest neighbor matching with a
- logistic regression-based propensity score, discarding control units
- outside the convex hull of the treated units
- \citep{KinZen06,KinZen07}:
-\begin{verbatim}
-> m.out <- matchit(treat ~ age + educ + black + hispan + nodegree +
- married + re74 + re75, method = "nearest", discard
- = "hull.control", data = lalonde)
-\end{verbatim}
- Then we check balance using the summary and plot procedures (which
- we don't show here). When the best balance is achieved,
- we run the parametric analysis:
-\begin{verbatim}
-> z.out <- zelig(re78 ~ treat + age + educ + black + hispan + nodegree +
- married + re74 + re75, data = match.data(m.out),
- model = "ls")
-\end{verbatim}
- and then set the explanatory variables at their means (the default)
- and change the treatment variable from a 0 to a 1:
-\begin{verbatim}
-> x.out <- setx(z.out, treat=0)
-> x1.out <- setx(z.out, treat=1)
-\end{verbatim}
-and finally compute the result and examine a summary:
-\begin{verbatim}
-> s.out <- sim(z.out, x = x.out, x1 = x1.out)
-> summary(s.out)
-\end{verbatim}
-
-\item[Average Treatment Effect on the Treated] We illustrate now how
- to estimate the average treatment effect on the treated in a way
- that is quite robust. We do this by estimating the coefficients in
- the control group alone.
-
- We begin by conducting nearest neighbor matching with a logistic
- regression-based propensity score:
-\begin{verbatim}
-> m.out1 <- matchit(treat ~ age + educ + black + hispan + nodegree +
- married + re74 + re75, method = "nearest", data = lalonde)
-\end{verbatim}
- Then we check balance using the summary and plot procedures (which
- we don't show here). We reestimate the matching procedure until we
- achieve the best balance possible. (The running examples here are
- meant merely to illustrate, not to suggest that we've achieved the
- best balance.) Then we go to Zelig, and in this case choose to fit
- a linear least squares model to the control group only:
-\begin{verbatim}
-> z.out1 <- zelig(re78 ~ age + educ + black + hispan + nodegree +
- married + re74 + re75, data = match.data(m.out1, "control"),
- model = "ls")
-\end{verbatim}
- where the {\tt "control"} option in {\tt match.data()} extracts only
- the matched control units and {\tt ls} specifies least squares
- regression. In a smaller data set, this example should probably be
- changed to include all the data in this estimation (using
- \texttt{data = match.data(m.out1)} for the data) and by including
- the treatment indicator (which is excluded in the example since its
- a constant in the control group.) Next, we use the coefficients
- estimated in this way from the control group, and combine them with
- the values of the covariates set to the values of the treated units.
- We do this by choosing conditional prediction (which means use the
- observed values) in \texttt{setx()}. The {\tt sim()} command does
- the imputation.
-\begin{verbatim}
-> x.out1 <- setx(z.out1, data = match.data(m.out1, "treat"), cond = TRUE)
-> s.out1 <- sim(z.out1, x = x.out1)
-\end{verbatim}
-Finally, we obtain a summary of the results by
-\begin{verbatim}
-> summary(s.out1)
-\end{verbatim}
-
-\item[Average Treatment Effect (Overall)] To estimate the average
- treatment effect, we continue with the previous example and fit the
- linear model to the {\it treatment group}:
-\begin{verbatim}
-> z.out2 <- zelig(re78 ~ age + educ + black + hispan + nodegree +
- married + re74 + re75, data = match.data(m.out1, "treat"),
- model = "ls")
-\end{verbatim}
-We then conduct the same simulation procedure in order to impute the
-counterfactual outcome for the {\it control group},
-\begin{verbatim}
-> x.out2 <- setx(z.out2, data = match.data(m.out1, "control"), cond = TRUE)
-> s.out2 <- sim(z.out2, x = x.out2)
-\end{verbatim}
-In this calculation, Zelig is computing the difference between
-observed and the expected values. This means that the treatment
-effect for the control units is the effect of control (observed
-control outcome minus the imputed outcome under treatment from the
-model). Hence, to combine treatment effects just reverse the signs of
-the estimated treatment effect of controls.
-\begin{verbatim}
-> ate.all <- c(s.out1$qi$att.ev, -s.out2$qi$att.ev)
-\end{verbatim}
-The point estimate, its standard error, and the $95\%$ confidence
-interval is given by
-\begin{verbatim}
-> mean(ate.all)
-> sd(ate.all)
-> quantile(ate.all, c(0.025, 0.975))
-\end{verbatim}
-
-\item[Subclassification] In subclassification, the average treatment
- effect estimates are obtained separately for each subclass, and then
- aggregated for an overall estimate. Estimating the treatment
- effects separately for each subclass, and then aggregating across
- subclasses, can increase the robustness of the ultimate results
- since the parametric analysis within each subclass requires only
- local rather than global assumptions. However, fewer observations
- are obviously available within each subclass, and so this option is
- normally chosen for larger data sets.
-
- We begin this example by conducting subclassification with four
- subclasses,
-\begin{verbatim}
-> m.out2 <- matchit(treat ~ age + educ + black + hispan + nodegree +
- married + re74 + re75, data = lalonde,
- method = "subclass", subclass = 4)
-\end{verbatim}
- When balance is as good as we can get it, we then fit a linear
- regression within each subclass by controlling for the estimated
- propensity score (called \texttt{distance}) and other covariates.
- In most software, this would involve running four separate
- regressions and then combining the results. In Zelig, however, all
- we need to do is to use the {\tt by} option:
-\begin{verbatim}
-> z.out3 <- zelig(re78 ~ re74 + re75 + distance,
- data = match.data(m.out2, "control"),
- model = "ls", by = "subclass")
-\end{verbatim}
- The same set of commands as in the first example are used to do the
- imputation of the counterfactual outcomes for the treated units:
-\begin{verbatim}
-> x.out3 <- setx(z.out3, data = match.data(m.out2, "treat"), fn = NULL,
- cond = TRUE)
-> s.out3 <- sim(z.out3, x = x.out3)
-> summary(s.out3)
-\end{verbatim}
-It is also possible to get the summary result for each subclass. For
-example, the following command summarizes the result for the second
-subclass.
-\begin{verbatim}
-> summary(s.out3, subset = 2)
-\end{verbatim}
-
-\item[How Adjustment After Exact Matching Has No Effect] Regression
-adjustment after exact one-to-one exact matching gives the identical
-answer as a simple, unadjusted difference in means. General exact
-matching, as implemented in MatchIt, allows one-to-many matches, so to see
-the same result we must weight when adjusting. In other words: weighted
-regression adjustment after general exact matching gives the identical
-answer as a simple, unadjusted weighted difference in means. For
-example:
-
-\begin{verbatim}
-> m.out <- matchit(treat ~ educ + black + hispan, data = lalonde,
- method = "exact")
-> m.data <- match.data(m.out)
-> ## weighted diff in means
-> weighted.mean(mdata$re78[mdata$treat == 1], mdata$weights[mdata$treat==1])
- - weighted.mean(mdata$re78[mdata$treat==0], mdata$weights[mdata$treat==0])
-[1] 807
-> ## weighted least squares without covariates
-> zelig(re78 ~ treat, data = m.data, model = "ls", weights = "weights")
-
-Call:
-zelig(formula = re78 ~ treat, model = "ls", data = m.data, weights =
-"weights")
-
-Coefficients:
-(Intercept) treat
- 5524 807
-
-> ## weighted least squares with covariates
-> zelig(re78 ~ treat + black + hispan + educ, data = m.data, model = "ls",
- weights = "weights")
-
-Call:
-zelig(formula = re78 ~ treat + black + hispan + educ, model = "ls",
-data = m.data, weights = "weights")
-
-Coefficients:
-(Intercept) treat black hispan educ
- 314 807 -1882 258 657
-\end{verbatim}
-
-
- \end{description}
-
-
-%%% Local Variables:
-%%% mode: latex
-%%% TeX-master: "matchit"
-%%% End:
diff --git a/vignettes/matchitref.tex b/vignettes/matchitref.tex
deleted file mode 100644
index c17701a..0000000
--- a/vignettes/matchitref.tex
+++ /dev/null
@@ -1,393 +0,0 @@
-\subsubsection{Syntax}
-\begin{verbatim}
-> m.out <- matchit(formula, data, method = "nearest", verbose = FALSE, ...)
-\end{verbatim}
-
-\subsubsection{Arguments}
-
-\paragraph{Arguments for All Matching Methods}
-
-\begin{itemize}
-
-\item \texttt{formula}: formula used to calculate the distance measure
- for matching (e.g., the propensity score model). It takes the usual syntax of R formulas, {\tt treat
- \~\ x1 + x2}, where {\tt treat} is a binary treatment indicator,
- and {\tt x1} and {\tt x2} are the pre-treatment covariates. Both the
- treatment indicator and pre-treatment covariates must be contained
- in the same data frame, which is specified as {\tt data} (see
- below). All of the usual R syntax for formulas work here. For
- example, {\tt x1:x2} represents the first order interaction term
- between {\tt x1} and {\tt x2}, and {\tt I(x1 \^\ 2)} represents the
- square term of {\tt x1}. See {\tt help(formula)} for details.
-
-\item \texttt{data}: the data frame containing the variables called in
- {\tt formula}.
-
-\item \texttt{method}: the matching method (default =
- \texttt{"nearest"}, nearest neighbor matching). Currently,
- \texttt{"exact"} (exact matching), \texttt{"full"} (full matching),
- \texttt{"nearest"} (nearest neighbor matching), \texttt{"optimal"}
- (optimal matching), \texttt{"subclass"} (subclassification),
- \texttt{"genetic"} (genetic matching), and \texttt{"cem"} (coarsened
- exact matching) are available. Note that within each of these
- matching methods, \MatchIt\ offers a variety of options. See below
- for more details.
-
-\item \texttt{verbose}: a logical value indicating whether to print
- the status of the matching algorithm (default = \texttt{FALSE}).
-\end{itemize}
-
-
-\paragraph{Additional Arguments for Specification of
- Distance Measures}
-\label{subsubsec:inputs-all}
-
-The following arguments specify distance measures that are used for
-matching methods. These arguments apply to all matching methods {\it
- except exact matching}.
-
-\begin{itemize}
-
-\item \texttt{distance}: the method used to estimate the distance
- measure (default = {\tt "logit"}, logistic regression) or a
- numerical vector of user's own distance measure. Before using any
- of these techniques, it is best to understand the theoretical
- groundings of these techniques and to evaluate the results. Most of
- these methods (such as logistic or probit regression) define the
- distance by first estimating the propensity score, defined as the
- probability of receiving treatment, conditional on the covariates.
- Available methods include:
- \begin{itemize}
- \item {\tt "mahalanobis"}: the Mahalanobis distance measure.
- \item binomial generalized linear models with one of the following
- link functions:
- \begin{itemize}
- \item \texttt{"logit"}: logistic link
- \item {\tt "linear.logit"}: logistic link with linear propensity
- score\footnote{The linear propensity scores are obtained by
- transforming back onto a linear scale.}
- \item \texttt{"probit"}: probit link
- \item {\tt "linear.probit"}: probit link with linear propensity
- score
- \item {\tt "cloglog"}: complementary log-log link
- \item {\tt "linear.cloglog"}: complementary log-log link with linear
- propensity score
- \item {\tt "log"}: log link
- \item {\tt "linear.log"}: log link with linear propensity score
- \item {\tt "cauchit"} Cauchy CDF link
- \item {\tt "linear.cauchit"} Cauchy CDF link with linear propensity
- score
- \end{itemize}
- \item Choose one of the following generalized additive models (see
- {\tt help(gam)} for more options).
- \begin{itemize}
- \item \texttt{"GAMlogit"}: logistic link
- \item {\tt "GAMlinear.logit"}: logistic link with linear propensity
- score
- \item \texttt{"GAMprobit"}: probit link
- \item {\tt "GAMlinear.probit"}: probit link with linear propensity
- score
- \item {\tt "GAMcloglog"}: complementary log-log link
- \item {\tt "GAMlinear.cloglog"}: complementary log-log link with
- linear propensity score
- \item {\tt "GAMlog"}: log link
- \item {\tt "GAMlinear.log"}: log link with linear propensity score,
- \item {\tt "GAMcauchit"}: Cauchy CDF link
- \item {\tt "GAMlinear.cauchit"}: Cauchy CDF link with linear
- propensity score
-\end{itemize}
-\item \texttt{"nnet"}: neural network model. See {\tt help(nnet)} for
- more options.
-\item \texttt{"rpart"}: classification trees. See {\tt help(rpart)}
- for more options.
- \end{itemize}
-
-\item \texttt{distance.options}: optional arguments for estimating the
- distance measure. The input to this argument should be a list. For
- example, if the distance measure is estimated with a logistic
- regression, users can increase the maximum IWLS iterations by
- \texttt{distance.options = list(maxit = 5000)}. Find additional
- options for general linear models using {\tt help(glm)} or {\tt
- help(family)}, for general additive models using {\tt help(gam)},
- for neutral network models {\tt help(nnet)}, and for classification
- trees {\tt help(rpart)}.
-
-\item \texttt{discard}: specifies whether to discard units that fall
- outside some measure of support of the distance measure (default =
- \texttt{"none"}, discard no units). Discarding units may change the
- quantity of interest being estimated by changing the observations left in the analysis.
- Enter a logical vector
- indicating which unit should be discarded or choose from the
- following options:
- \begin{itemize}
- \item \texttt{"none"}: no units will be discarded before matching.
- Use this option when the units to be matched are substantially
- similar, such as in the case of matching treatment and control
- units from a field experiment that was close to (but not fully)
- randomized (e.g., \citealt{Imai05}), when caliper matching will
- restrict the donor pool, or when you do not wish to change the
- quantity of interest and the parametric methods to be used
- post-matching can be trusted to extrapolate.
- \item \texttt{"hull.both"}: all units that are not within the convex
- hull will be discarded. See \citet{KinZen06,KinZen07} for
- information about the convex hull in this context and as a measure
- of model dependence.
- \item \texttt{"both"}: all units (treated and control) that are
- outside the support of the distance measure will be discarded.
- \item \texttt{"hull.control"}: only control units that are not
- within the convex hull of the treated units will be discarded.
- \item \texttt{"control"}: only control units outside the support of
- the distance measure of the treated units will be discarded. Use
- this option when the average treatment effect on the treated is of
- most interest and when you are unwilling to discard
- non-overlapping treatment units (which would change the quantity
- of interest).
- \item \texttt{"hull.treat"}: only treated units that are not within
- the convex hull of the control units will be discarded.
- \item \texttt{"treat"}: only treated units outside the support of
- the distance measure of the control units will be discarded. Use
- this option when the average treatment effect on the control units
- is of most interest and when unwilling to discard control units.
- \end{itemize}
-
-\item \texttt{reestimate}: If {\tt FALSE} (default), the model for the
- distance measure will not be re-estimated after units are discarded.
- The input must be a logical value. Re-estimation may be desirable
- for efficiency reasons, especially if many units were discarded and
- so the post-discard samples are quite different from the original
- samples.
-
-\end{itemize}
-
-\paragraph{Additional Arguments for Subclassification}
-\label{subsubsec:inputs-subclass}
-
-\begin{itemize}
-\item \texttt{sub.by}: criteria for subclassification. Choose from:
- \texttt{"treat"} (default), the number of treatment units;
- \texttt{"control"}, the number of control units; or \texttt{"all"},
- the total number of units. Changing the default will likely also
- signal a change in your quantity of interest from the average
- treatment effect on the treated to other quantities.
-\item \texttt{subclass}: either a scalar specifying the number of
- subclasses, or a vector of probabilities bounded between 0 and 1,
- which create quantiles of the distance measure using the units in
- the group specified by \texttt{sub.by} (default = \texttt{subclass =
- 6}).
-\end{itemize}
-
-\paragraph{Additional Arguments for Nearest Neighbor Matching}
-\label{subsubsec:inputs-nearest}
-
-\begin{itemize}
-\item \texttt{m.order}: the order in which to match treatment units
- with control units.
- \begin{itemize}
- \item {\tt "largest"} (default): matches from the largest value of
- the distance measure to the smallest.
- \item {\tt "smallest"}: matches from the smallest value of the
- distance measure to the largest.
- \item {\tt "random"}: matches in random order.
- \end{itemize}
-\item \texttt{replace}: logical value indicating whether each control
- unit can be matched to more than one treated unit (default = {\tt
- replace = FALSE}, each control unit is used at most once -- i.e.,
- sampling without replacement). For matching with replacement, use
- \texttt{replace = TRUE}. After matching with replacement, the weights
- can be used to reflect the frequency with which each control unit was matched.
-\item \texttt{ratio}: the number of control units to match to each
- treated unit (default = {\tt 1}). If matching is done without
- replacement and there are fewer control units than {\tt ratio} times
- the number of eligible treated units (i.e., there are not enough
- control units for the specified method), then the higher ratios will
- have \texttt{NA} in place of the matching unit number in
- \texttt{match.matrix}.
-\item \texttt{exact}: variables on which to perform exact matching
- within the nearest neighbor matching (default = {\tt NULL}, no exact
- matching). If \texttt{exact} is specified, only matches that
- exactly match on the covariates in \texttt{exact} will be allowed.
- Within the matches that match on the variables in \texttt{exact},
- the match with the closest distance measure will be chosen.
- \texttt{exact} should be entered as a vector of variable names
- (e.g., \texttt{exact = c("X1", "X2")}).
-\item \texttt{caliper}: the number of standard deviations of the
- distance measure within which to draw control units (default = {\tt
- 0}, no caliper matching). If a caliper is specified, a control
- unit within the caliper for a treated unit is randomly selected as
- the match for that treated unit. If \texttt{caliper != 0}, there
- are two additional options:
- \begin{itemize}
- \item \texttt{calclosest}: whether to take the nearest available
- match if no matches are available within the \texttt{caliper}
- (default = {\tt FALSE}).
- \item \texttt{mahvars}: variables on which to perform
- Mahalanobis-metric matching within each caliper (default = {\tt
- NULL}). Variables should be entered as a vector of variable
- names (e.g., \texttt{mahvars = c("X1", "X2")}). If
- \texttt{mahvars} is specified without \texttt{caliper}, the
- caliper is set to 0.25.
- \end{itemize}
-\item \texttt{subclass} and \texttt{sub.by}: See the options for
- subclassification for more details on these options. If a
- \texttt{subclass} is specified within \texttt{method = "nearest"},
- the matched units will be placed into subclasses after the nearest
- neighbor matching is completed.
-\end{itemize}
-
-\paragraph{Additional Arguments for Optimal Matching}
-\label{subsubsec:inputs-optimal}
-
-\begin{itemize}
-\item {\tt ratio}: the number of control units to be matched to each
- treatment unit (default = {\tt 1}).
-\item {\tt ...}: additional inputs that can be passed to the {\tt
- fullmatch()} function in the {\tt optmatch} package. See {\tt
- help(fullmatch)} or
- \hlink{http://www.stat.lsa.umich.edu/\~{}bbh/optmatch.html}{http://www.stat.lsa.umich.edu/~bbh/optmatch.html}
- for details.
-\end{itemize}
-
-\paragraph{Additional Arguments for Full Matching}
-\label{subsubsec:inputs-full}
-
-See {\tt help(fullmatch)} (part of this information is copied below)
-or
-\hlink{http://www.stat.lsa.umich.edu/\~{}bbh/optmatch.html}{http://www.stat.lsa.umich.edu/~bbh/optmatch.html}
-for details.
-
-\begin{itemize}
-\item {\tt min.controls}: The minimum ratio of controls to treatments
- that is to be permitted within a matched set: should be nonnegative
- and finite. If {\tt min.controls} is not a whole number, the
- reciprocal of a whole number, or zero, then it is rounded down to
- the nearest whole number or reciprocal of a whole number.
-
-\item {\tt max.controls}: The maximum ratio of controls to treatments
- that is to be permitted within a matched set: should be positive and
- numeric. If {\tt max.controls} is not a whole number, the reciprocal
- of a whole number, or {\tt Inf}, then it is rounded up to the
- nearest whole number or reciprocal of a whole number.
-
-\item {\tt omit.fraction}: Optionally, specify what fraction of
- controls or treated subjects are to be rejected. If {\tt
- omit.fraction} is a positive fraction less than one, then {\tt
- fullmatch()} leaves up to that fraction of the control reservoir
- unmatched. If {\tt omit.fraction} is a negative number greater than
- $-1$, then {\tt fullmatch()} leaves up to $|{\rm omit.fraction}|$ of
- the treated group unmatched. Positive values are only accepted if
- ${\rm max.controls} >= 1$; negative values, only if ${\rm
- min.controls} <= 1$. If {\tt omit.fraction} is not specified,
- then only those treated and control subjects without permissible
- matches among the control and treated subjects, respectively, are
- omitted.
-
-\item {\tt ...}: Additional inputs that can be passed to the {\tt
- fullmatch()} function in the {\tt optmatch} package.
-\end{itemize}
-
-\paragraph{Additional Arguments for Genetic Matching}
-\label{subsubsec:inputs-genetic}
-
-The available options are listed below.
-\begin{itemize}
-\item {\tt ratio}: the number of control units to be matched to each
- treatment unit (default = {\tt 1}).
-\item {\tt ...}: additional minor inputs that can be passed to the
- {\tt GenMatch()} function in the {\tt Matching} package. See {\tt
- help(GenMatch)} or\\
- \hlink{http://sekhon.polisci.berkeley.edu/library/Matching/html/GenMatch.html}{http://sekhon.polisci.berkeley.edu/library/Matching/html/GenMatch.html}
- for details.
-\end{itemize}
-
-\paragraph{Additional Arguments for Coarsened Exact Matching}
-\label{subsubsec:inputs-cem}
-
-The available options are listed here:
-\begin{itemize}
-\item{cutpoints} named list each describing the cutpoints for the
- variables. Each list element is either a vector of cutpoints, a
- number of cutpoints, a method for automatic bin contruction.
-\item{k2k} return k-to-k matching?
-\item{verbose} controls level of verbosity
-\item{dist} user defined distance function
-\item {\tt ...}: additional minor inputs that can be passed to the
- {\tt cem()} function in the {\tt cem} package. See {\tt
- help(cem)} or
- \hlink{http://gking.harvard.edu/cem}{http://gking.harvard.edu/cem}
- for details.
-\end{itemize}
-
-\subsubsection{Output Values}
-\label{sec:outputs}
-
-Regardless of the type of matching performed, the \texttt{matchit}
-output object contains the following elements:\footnote{When
- inapplicable or unnecessary, these elements may equal {\tt NULL}.
- For example, when exact matching, {\tt match.matrix = NULL}.}
-
-\begin{itemize}
-\item \texttt{call}: the original {\tt matchit()} call.
-
-\item \texttt{formula}: the formula used to specify the model for
- estimating the distance measure.
-
-\item \texttt{model}: the output of the model used to estimate
- the distance measure. \texttt{summary(m.out\$model)} will give the
- summary of the model where \texttt{m.out} is the output object from
- \texttt{matchit()}.
-
-\item \texttt{match.matrix}: an $n_1 \times$ \texttt{ratio} matrix
- where:
- \begin{itemize}
- \item the row names represent the names of the treatment units
- (which match the row names of the data frame specified in
- \texttt{data}).
- \item each column stores the name(s) of the control unit(s) matched
- to the treatment unit of that row. For example, when the
- \texttt{ratio} input for nearest neighbor or optimal matching is
- specified as 3, the three columns of \texttt{match.matrix}
- represent the three control units matched to one treatment unit).
- \item \texttt{NA} indicates that the treatment unit was not matched.
- \end{itemize}
-
-\item \texttt{discarded}: a vector of length $n$ that displays whether
- the units were ineligible for matching due to common support
- restrictions. It equals \texttt{TRUE} if unit $i$ was discarded,
- and it is set to \texttt{FALSE} otherwise.
-
-\item \texttt{distance}: a vector of length $n$ with the estimated
- distance measure for each unit.
-
-\item \texttt{weights}: a vector of length $n$ with the weights
- assigned to each unit in the matching process. Unmatched units have
- weights equal to $0$. Matched treated units have weight $1$. Each
- matched control unit has weight proportional to the number of
- treatment units to which it was matched, and the sum of the control
- weights is equal to the number of uniquely matched control units.
-
-\item \texttt{subclass}: the subclass index in an ordinal scale from 1
- to the total number of subclasses as specified in \texttt{subclass}
- (or the total number of subclasses from full or exact matching).
- Unmatched units have \texttt{NA}.
-
-\item \texttt{q.cut}: the subclass cut-points that classify the
- distance measure.
-
-\item \texttt{treat}: the treatment indicator from \texttt{data} (the
- left-hand side of \texttt{formula}).
-
-\item \texttt{X}: the covariates used for estimating the distance
- measure (the right-hand side of \texttt{formula}). When applicable,
- \texttt{X} is augmented by covariates contained in \texttt{mahvars}
- and \texttt{exact}.
-
-\item \texttt{nn}: A basic summary table of matched data (e.g., the
- number of matched units)
-
-\end{itemize}
-
-
-%%% Local Variables:
-%%% mode: latex
-%%% TeX-master: "matchit"
-%%% End:
diff --git a/vignettes/mdataref.tex b/vignettes/mdataref.tex
deleted file mode 100644
index 975d076..0000000
--- a/vignettes/mdataref.tex
+++ /dev/null
@@ -1,103 +0,0 @@
-\section{\texttt{match.data()}: Extracting the Matched Data Set}
-\label{sec:match.data}
-
-\subsection{Usage}
-
-To extract the matched data set for subsequent analyses from the
-output object (see Section~\ref{sec:analysis}), we provide the
-function {\tt match.data()}. This is used as follows:
-
-\begin{verbatim}
-> m.data <- match.data(object, group = "all", distance = "distance",
- weights = "weights", subclass = "subclass")
-\end{verbatim}
-
-The output of the function {\tt match.data()} is the original data
-frame where additional information about matching (i.e., distance
-measure as well as resulting weights and subclasses) is added,
-restricted to units that were matched.
-
-\subsection{Arguments}
-
-{\tt match.data()} takes the following inputs:
-\begin{enumerate}
-\item {\tt object} is the output object from {\tt matchit()}. This is
- a required input.
-\item {\tt group} specifies for which matched group the user wants to
- extract the data. Available options are {\tt "all"} (all matched
- units), {\tt "treat"} (matched units in the treatment group), and
- {\tt "control"} (matched units in the control group). The default is
- {\tt "all"}.
-\item {\tt distance} specifies the variable name used to store the
- distance measure. The default is {\tt "distance"}.
-\item {\tt weights} specifies the variable name used to store the
- resulting weights from matching. The default is {\tt "weights"}. See
- Section~\ref{subsec:weights} for more details on the weights.
-\item {\tt subclass} specifies the variable name used to store the
- subclass indicator. The default is {\tt "subclass"}.
-\end{enumerate}
-
-\subsection{Examples}
-
-Here, we present examples for using {\tt match.data()}. Users can run
-these commands by typing {\tt demo(match.data)} at the R
-prompt. First, we load the Lalonde data,
-
-\begin{verbatim}
-> data(lalonde)
-\end{verbatim}
-
-The next line performs nearest neighbor matching based on the
-estimated propensity score from the logistic regression,
-
-\begin{verbatim}
-> m.out1 <- matchit(treat ~ re74 + re75 + age + educ, data = lalonde,
-+ method = "nearest", distance = "logit")
-\end{verbatim}
-
-To obtain matched data, type the following command,
-
-\begin{verbatim}
-> m.data1 <- match.data(m.out1)
-\end{verbatim}
-
-It is easy to summarize the resulting matched data,
-
-\begin{verbatim}
-> summary(m.data1)
-\end{verbatim}
-
-To obtain matched data for the treatment or control group, specify the option
-{\tt group} as follows,
-
-\begin{verbatim}
-> m.data2 <- match.data(m.out1, group = "treat")
-> summary(m.data2)
-> m.data3 <- match.data(m.out1, group = "control")
-> summary(m.data3)
-\end{verbatim}
-
-We can also use the function to return unmatched data:
-
-\begin{verbatim}
-> unmatched.data <- lalonde[!row.names(lalonde)%in%row.names(match.data(m.out1)),]
-\end{verbatim}
-
-We can also specify different names for the subclass indicator, the
-weight variable, and the estimated distance measure. The following
-example first does a subclassification method, obtains the
-matched data with specified names for those three variables, and then
-print out the names of all variables in the resulting matched data.
-
-\begin{verbatim}
-> m.out2 <- matchit(treat ~ re74 + re75 + age + educ, data = lalonde,
-+ method = "subclass")
-> m.data4 <- match.data(m.out2, subclass = "block", weights = "w",
-+ distance = "pscore")
-> names(m.data4)
-\end{verbatim}
-
-%%% Local Variables:
-%%% mode: latex
-%%% TeX-master: "matchit"
-%%% End:
diff --git a/vignettes/notation.tex b/vignettes/notation.tex
deleted file mode 100644
index 4aaf294..0000000
--- a/vignettes/notation.tex
+++ /dev/null
@@ -1,151 +0,0 @@
-\documentclass[oneside,letterpaper,titlepage,12pt]{article}
-%\usepackage[ae,hyper]{/usr/lib/R/share/texmf/Rd}
-\usepackage{makeidx}
-\usepackage{graphicx}
-\usepackage{natbib}
-\usepackage[reqno]{amsmath}
-\usepackage{amssymb}
-\usepackage{verbatim}
-\usepackage{epsf}
-\usepackage{url}
-\usepackage{html}
-\usepackage{dcolumn}
-\usepackage{longtable}
-\usepackage{vmargin}
-\setpapersize{USletter}
-\newcolumntype{.}{D{.}{.}{-1}}
-\newcolumntype{d}[1]{D{.}{.}{#1}}
-%\pagestyle{myheadings}
-\htmladdtonavigation{
- \htmladdnormallink{%
- \htmladdimg{http://gking.harvard.edu/pics/home.gif}}
- {http://gking.harvard.edu/}}
-\newcommand{\hlink}{\htmladdnormallink}
-
-\bodytext{ BACKGROUND="http://gking.harvard.edu/pics/temple.setcounter"}
-\setcounter{tocdepth}{3}
-
-\parindent=0cm
-\newcommand{\MatchIt}{\textsc{MatchIt}}
-
-\begin{document}
-
-\begin{center}
-Notation for \MatchIt \\
-Elizabeth Stuart \\
-\end{center}
-
-This document details the notation to be used in the matching paper to accompany \MatchIt,
-as discussed in conference call on April 27, 2004 and emails on April 27-29, 2004. \\
-
-We first provide a general idea of the notation and ideas. Formal notation follows.
-
-\begin{enumerate}
-\item There exists in nature fixed values, $\theta_{1i}$ and $\theta_{0i}$, the
-potential outcomes under treatment and control, respectively. They, or
-more usually their difference, are our quantities of interest and hence
-the inferential target in this exercise. They are not generally known.
-There also exist in nature a vector of fixed values $X_i$ that are known and
-will play the role of covariates to condition on. Note that the use of $X_i$ in matching assumes that they are not
-affected by treatment assignment: $X_{1i}=X_{0i}=X_i$. If a researcher is interested in adjusting for a variable potentially affected by treatment
-assignment, then methods such as principal stratification should be used. [We can write a paragraph on that somewhere.]
-
-\item Then (i.e., only after step 1) $T_i$ is created, preferably by the
-experimenter, who assigns its values randomly, but in some cases $T_i$ is
-created by the world and we hope that it was created effectively randomly
-(or randomly conditional on the observed $X_i$). This is what is known as the assumption of
-unconfounded treatment assignment: That treatment assignment is independent of
-the potential outcomes given the covariates $X_i$.
-
-\item Finally, the observed outcome variable $Y_i$ is calculated
-deterministically as $Y_i = \theta_{1i}T_i + \theta_{0i}(1-T_i)$. This is
-an accounting identity, not a regression equation with an error term;
-i.e., it is just true, not really an assumption.
-\end{enumerate}
-
-The accounting identity in 3 implies that we observe $\theta_{1i}=Y_i$ (but
-not $\theta_{0i}$) when $T_i=1$, and we observe $\theta_{0i}=Y_i$ (but not
-$\theta_{1i}$) when $T_i=0$. Since the fundamental problem of causal
-inference indicates that either $\theta_{0i}$ or $\theta_{1i}$ will be
-unobserved for each $i$, we will need to infer their values, for which we
-define $\tilde\theta_{1i} \sim p(\theta_{1i})$ and $\tilde\theta_{0i} \sim
-p(\theta_{0i})$ as draws of the potential outcomes under treatment and
-control, respectively, from their respective predictive posterior
-distributions.\\
-
-We now detail the notation utilized. Fixed, but sometimes unknown values are represented by Greek letters. Draws from the posterior
-distribution of these unknown values are represented by a tilde over the variable of interest. Fixed, but always known values are represented
-by capital Roman letters.
-We first define notation for individual $i$:
-\begin{itemize}
-\item $\theta_{1i}=$ individual $i$'s potential outcome under treatment
-\item $\theta_{0i}=$ individual $i$'s potential outcome under control
-\item $T_i=$ individual $i$'s observed treatment assignment
-\begin{itemize} \item $T_i=1$ means individual $i$ receives treatment
- \item $T_i=0$ means individual $i$ receives control
-\end{itemize}
-\item $\theta_{0i}$ and $\theta_{1i}$ are considered fixed quantities. Which one is observed depends on the random variable $T_i$.
-\item $Y_i=T_i \theta_{1i} + (1-T_i) \theta_{0i}$ is individual $i$'s observed outcome
-\item Let $Y_{1i}=(\theta_{1i}|T_i=1)$. Similarly, $Y_{0i}=(\theta_{0i}|T_i=0)$. One of these is observed for individual $i$. [Do we actually want this
-notation? It's not quite right since the capital Roman letter would imply that $Y_{1i}$ is always observed, but the notation may be handy (see below).]
-\item Let $\tilde{\theta}_{0i}$ be a draw from the posterior distribution of $\theta_{0i}$: $\tilde{\theta}_{0i} \sim p(\theta_{0i})$.
-Similarly, let $\tilde{\theta}_{1i}$ be a draw from the posterior distribution of $\theta_{1i}$: $\tilde{\theta}_{1i} \sim p(\theta_{1i})$.
-\item Consider variables $X_i$. If $X_{0i}=X_{1i}=X_i$ then $X$ is a ``proper covariate'' in that it is not affected by treatment assignment. Only proper
-covariates should be used in the matching procedure. That $X_i$ is not affected by treatment assignment
-is always an assumption (sometimes more reasonable than other times)--we never observe $X_{0i}$ and $X_{1i}$ for individual $i$.
-\end{itemize}
-
-For individual $i$, the potentially observed values can be represented by the following 2x2 table:
-
-\begin{center}
-\begin{tabular}{cc|c|c|}
-\multicolumn{4}{c}{\hspace*{4cm} Actual treatment assignment} \\
-\\
-\multicolumn{2}{c}{} & \multicolumn{2}{c}{Control \hfill Treatment} \\
-\cline{3-4}
-& & & \phantom{abcd} \\
-& Control & $\theta_{0i}$, $X_i$ & $\tilde{\theta}_{0i}$, $X_i$ \\
-Potential & & & \phantom{abcd} \\
-\cline{3-4}
-outcomes under & & & \phantom{abcd} \\
-& Treatment & $\tilde{\theta}_{1i}$, $X_i$ & $\theta_{1i}$, $X_i$ \\
-& & & \phantom{abcd} \\
-\cline{3-4}
-\end{tabular}
-\end{center}
-
-For each individual, we are in either Column 1 or Column 2 (depending on treatment assignment). Within each column, 1 number will be observed and 1 will be a drawn
-value from the posterior distribution (i.e., the true value for that cell is missing). Thus, for each individual we are in the situation of one of the
-following two vectors of potential outcomes:
-
-\begin{center}
-\begin{tabular}{rl}
-If $T_i=1$: & $(\tilde\theta_{0i}, \theta_{1i})$ \\
-If $T_i=0$: & $(\theta_{0i}, \tilde\theta_{1i})$ \\
-\end{tabular}
-\end{center}
-
-Now consider $n$ individuals observed, with $n_1$ in the treated group and $n_0$ in the control group ($n=n_0+n_1$). Then we have the following notation:
-\begin{itemize}
-\item $n_1=\sum_{i=1}^n T_i$, $n_0=\sum_{i=1}^n (1-T_i)$
-\item ${\bf Y_0} = \{Y_{i}|T_i=0\}$. ${\bf Y_0}$ is of length $n_0$.
-\item ${\bf Y_1} = \{Y_{i}|T_i=1\}$. ${\bf Y_1}$ is of length $n_1$.
-\item ${\bf Y} = \{ {\bf Y_0}, {\bf Y_1}\}$. ${\bf Y}$ is of length $n$.
-\item $\overline{Y}_1 = \frac{\sum_{i=1}^n T_i \theta_{1i}}{\sum_{i=1}^n T_i}=\frac{\sum_{i=1}^{n_1} Y_{1i}}{n_1}$
-\item $\overline{Y}_0 = \frac{\sum_{i=1}^n (1-T_i) \theta_{0i}}{\sum_{i=1}^n (1-T_i)}=\frac{\sum_{i=1}^{n_0} Y_{0i}}{n_0}$
-\item Observed sample variances would be calculated in a similar way (using ${\bf Y_0}$ and ${\bf Y_1}$).
-\end{itemize}
-
-Throughout, we will use $p()$ to represent pdf's and $g()$ for functional forms of models.
-
-One point to make sure we mention in the write-up is to say what OLS assumes. OLS with a treatment indicator does:
-$$Y_i|X_i, T_i \sim N(\alpha + \beta_0 T_i + {\boldsymbol \beta} {\bf X_i}, \sigma^2)$$
-which assumes that the models of the potential outcomes follow parallel lines with equal residual variance:
-$$\theta_{1i}|X_i \sim N(\alpha + \beta_0 + {\boldsymbol \beta} {\bf X_i}, \sigma^2)$$
-$$\theta_{0i}|X_i \sim N(\alpha + {\boldsymbol \beta} {\bf X_i}, \sigma^2).$$
-We can also have a graphical representation of this, perhaps with some examples of outcomes that clearly don't have that nice parallel linear relationship,
-and show that this would be a very special case of what we're advocating.
-
-
-
-\end{document}
diff --git a/vignettes/overview.tex b/vignettes/overview.tex
deleted file mode 100644
index d44adc2..0000000
--- a/vignettes/overview.tex
+++ /dev/null
@@ -1,199 +0,0 @@
-
-\MatchIt\ is designed for causal inference with a dichotomous treatment
-variable and a set of pretreatment control variables. Any number or
-type of dependent variables can be used. (If you are interested in
-the causal effect of more than one variable in your data set, run
-\MatchIt\ separately for each one; it is unlikely in any event that
-any one parametric model will produce valid causal inferences for more
-than one treatment variable at a time.) \MatchIt\ can be used for
-other types of causal variables by dichotomizing them, perhaps in
-multiple ways \citep[see also][]{ImaDyk04}. \MatchIt\ works for
-experimental data, but is usually used for observational studies where
-the treatment variable is not randomly assigned by the investigator,
-or the random assignment goes awry.
-
-We adopt the same notation as in \citet*{HoImaKin07}. Unless
-otherwise noted, let $i$ index the $n$ units in the data set, $n_1$
-denote the number of treated units, $n_0$ denote the number of control
-units (such that $n=n_0+n_1$), and $x_i$ indicate a vector of
-pretreatment (or control) variables for unit $i$. Let $t_i=1$ when
-unit $i$ is assigned treatment, and $t_i=0$ when unit $i$ is assigned
-control. (The labels ``treatment'' and ``control'' and values 1 and 0
-respectively are arbitrary and can be switched for convenience, except
-that some methods of matching are keyed to the definition of the
-treated group.) Denote $y_i(1)$ as the potential outcome of unit $i$
-under treatment --- the value the outcome variable would take if $t_i$
-were equal to 1, whether or not $t_i$ in fact is 0 or 1 -- and
-$y_i(0)$ the potential outcome of unit $i$ under control --- the value
-the outcome variable would take if $t_i$ were equal to 0, regardless
-of its value in fact. The variables $y_i(1)$ and $y_i(0)$ are jointly
-unobservable, and for each $i$, we observe one
-$y_i=t_iy_i(1)+(1-t_i)y_i(0)$, and not the other.
-
-Also denote a fixed vector of exogenous, pretreatment measured
-confounders as $X_i$. These variables are defined in the hope or
-under the assumption that conditioning on them appropriately will make
-inferences ignorable. Measures of balance should be computed with
-respect to all of $X$, even if some methods of matching only use some
-components.
-
-\section{Preprocessing via Matching}
-
-If $t_i$ and $X_i$ were independent, we would not need to control for
-$X_i$, and any parametric analysis would effectively reduce to a
-difference in means of $Y$ for the treated and control groups. The
-goal of matching is to preprocess the data prior to the parametric
-analysis so that the actual relationship between $t_i$ and $X_i$ is
-eliminated or reduced without introducing bias and or increasing
-inefficiency too much.
-
-When matching we select, duplicate, or selectively drop observations
-from our data, and we do so without inducing bias as long as we use a
-rule that is a function only of $t_i$ and $X_i$ and does not depend on
-the outcome variable $Y_i$. Many methods that offer this
-preprocessing are included here, including exact, subclassification,
-nearest neighbor, optimal, and genetic
-matching. For many of these methods the propensity score--defined as the
-probability of receiving the treatment given the covariates--is a key tool.
-In order to avoid changing the quantity of interest, most
-\MatchIt\ routines work by retaining all treated units and selecting (or weighting)
-control units to include in the final data set; this enables
-one to estimate the average treatment effect on the treated (the purpose
-of which is described in Section \ref{s:qoi}).
-
-\MatchIt\ implements and evaluates the choice of the rules for
-matching. Matching sometimes increases efficiency by eliminating
-heterogeneity or deleting observations outside of an area where a
-model can reasonably be used to extrapolate, but one needs to be
-careful not to lose too many observations in matching or efficiency
-will drop more than the reduction in bias that is achieved.
-
-The simplest way to obtain good matches (as defined above) is to use
-one-to-one exact matching, which pairs each treated unit with one
-control unit for which the values of $X_i$ are identical. However,
-with many covariates and finite numbers of potential matches,
-sufficient exact matches often cannot be found. Indeed, many of the
-other methods implemented in \MatchIt\ attempt to balance the overall
-covariate distributions as much as possible, when sufficient
-one-to-one exact matches are not available.
-
-A key point in \citet*{HoImaKin07} is that matching methods by
-themselves are not methods of estimation: Every use of matching in the
-literature involves an analysis step following the matching procedure,
-but almost all analyses use a simple difference in means. This
-procedure is appropriate only if exact matching was conducted. In
-almost all other cases, some adjustment is required, and there is no
-reason to degrade your inferences by using an inferior method of
-analysis such as a difference in means even when improving your
-inferences via preprocessing. Thus, with \MatchIt, you can improve
-your analyses in two ways. \MatchIt\ analyses are ``doubly
-robust'' in that if \emph{either} the matching analysis \emph{or} the
-analysis model is correct (but not necessarily both) your inferences
-will be statistically consistent. In practice, the modeling choices
-you make at the analysis stage will be much less consequential if you
-match first.
-
-\section{Checking Balance}
-\label{sec:balance-sum}
-
-The goal of matching is to create a data set that looks closer to one
-that would result from a perfectly blocked (and possibly randomized)
-experiment. When we get close, we break the link between the treatment
-variable and the pretreatment controls, which makes the parametric
-form of the analysis model less relevant or irrelevant entirely. To
-break this link, we need the distribution of covariates to be the same
-within the matched treated and control groups.
-
-A crucial part of any matching procedure is, therefore, to assess how
-close the (empirical) covariate distributions are in the two groups,
-which is known as ``balance.'' Because the outcome variable is not
-used in the matching procedure, any number of matching methods can be
-tried and evaluated, and the one matching procedure that leads to the
-best balance can be chosen. \MatchIt\ provides a number of ways to
-assess the balance of covariates after matching, including numerical
-summaries such as the ``mean Diff.'' (difference in means) or the
-difference in means divided by the treated group standard deviation,
-and summaries based on quantile-quantile plots that compare the
-empirical distributions of each covariate. The widely used procedure
-of doing t-tests of the difference in means is highly misleading and
-should never be used to assess balance; see \citet{ImaKinStu08}.
-
-These balance diagnostics should be performed on all variables in $X$,
-even if some are excluded from one of the matching procedures.
-
-\section{Conducting Analyses after Matching}\label{s:qoi}
-
-The most common way that parametric analyses are used to compute
-quantities of interest (without matching) is by (statistically)
-holding constant some explanatory variables, changing others, and
-computing predicted or expected values and taking the difference or
-ratio, all by using the parametric functional form. In the case of
-causal inference, this would mean looking at the effect on the
-expected value of the outcome variable when changing $T$ from 0 to 1,
-while holding constant the pretreatment control variables $X$ at their
-means or medians. This, and indeed any other appropriate analysis
-procedure, would be a perfectly reasonable way to proceed with
-analysis after matching. If it is the chosen way to proceed, then
-either treated or control units may be deleted during the matching
-stage, since the same parametric structure is assumed to apply to all
-observations.
-
-In other instances, researchers wish to reduce the assumptions
-inherent in their statistical model and so want to allow for the
-possibility that their treatment effect to vary over observations. In
-this situation, one popular quantity of interest used is the
-\emph{average treatment effect on the treated} (ATT). For example,
-for the treated group, the potential outcomes under control, $Y_i(0)$,
-are missing, whereas the outcomes under treatment, $Y_i(1)$, are
-observed, and the goal of the analysis is to impute the missing
-outcomes, $Y_i(0)$ for observations with $T_i=1$. We do this via
-simulation using a parametric statistical model such as regression,
-logit, or others (as described below). Once those potential outcomes
-are imputed from the model, the estimate of individual $i$'s treatment
-effect is $Y_i(1)-\widehat{Y}_i(0)$ where $\widehat{Y}_i(0)$ is a
-predicted value of the dependent variable for unit $i$ under the
-counterfactual condition where $T_i=0$. The in-sample average
-treatment effect for the treated individuals can then be obtained by
-averaging this difference over all observations $i$ where in fact
-$T_i=1$. Most \MatchIt\ algorithms retain all treated units, and
-choose some subset of or repeated units from the control group, so
-that estimating the ATT is straightforward. If one chooses options
-that allow matching with replacement, or any solution that has
-different numbers of controls (or treateds) within each subclass or strata (such
-as full matching),
-then the parametric analysis following matching must accomodate these
-procedures, such as by using fixed effects or weights, as appropriate.
-(Similar procedures can also be used to estimate various other
-quantities of interest such as the average treatment effect by
-computing it for all observations, but then one must be aware that the
-quantity of interest may change during the matching procedure
-as some control units may be dropped.)
-
-The imputation from the model can be done in at least two ways.
-Recall that the model is used to impute \emph{the value that the
- outcome variable would take among the treated units if those treated
- units were actually controls}. Thus, one reasonable approach would
-be to fit a model to the matched data and create simulated predicted
-values of the dependent variable for the treated units with $T_i$
-switched counterfactually from 1 to 0. An alternative approach would
-be to fit a model without $T$ by using only the outcomes of the
-matched control units (i.e., using only observations where $T_i=0$).
-Then, given this fitted model, the missing outcomes $Y_i(0)$ are
-imputed for the matched treated units by using the values of the
-explanatory variables for the treated units. The first approach will
-usually have lower variance, since all observations are used, and the
-second may have less bias, since no assumption of constant parameters
-across the models of the potential outcomes under treatment and control is needed.
-See \citet*{HoImaKin07} for more details.
-
-Other quantities of interest can also be computed at the parametric
-stage, following any procedures you would have followed in the absence
-of matching. The advantage is that if matching is done well your
-answers will be more robust to many small changes in parametric
-specification.
-
-
-%%% Local Variables:
-%%% mode: latex
-%%% TeX-master: "matchit"
-%%% End:
diff --git a/vignettes/plotref.tex b/vignettes/plotref.tex
deleted file mode 100644
index 4743c0a..0000000
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+++ /dev/null
@@ -1,105 +0,0 @@
-\section{\texttt{plot()}: Graphical Summaries of Balance}
-
-
-\subsection{Plot options for the matchit object}
-The \texttt{plot()} command allows you to check the distributions of
-propensity scores and covariates in the assignment model, squares, and
-interactions, and within each subclasses if specified.
-
-\subsubsection{Syntax}
-
-\begin{verbatim}
-> plot(m.out, discrete.cutoff = 5, type = "QQ",
- numdraws = 5000, interactive = TRUE, which.xs = NULL, ...)
-\end{verbatim}
-
-\subsubsection{Arguments}
-
-\begin{itemize}
-\item {\tt type}: type of output graph. \texttt{type = "QQ"}
- (default) outputs empirical quantile-quantile plots of each
- covariate to check balance of marginal distributions. Alternatively,
- \texttt{type = "jitter"} outputs jitter plots of the propensity
- score for treated and control units. Finally, \texttt{type="hist"} outputs
- histograms of the propensity score in the original treated and control groups
- and weighted histograms of the propensity score in the matched treated and control groups.
-
-\item {\tt discrete.cutoff}: For quantile-quantile plots, discrete
- covariates that take 5 or fewer values are jittered for visibility.
- This may be changed by setting this argument to any other positive
- integer.
-
-\item {\tt interactive}: If \texttt{TRUE} (default), users can
- identify individual units by clicking on the graph with the left
- mouse button, and (when applicable) choose subclasses to plot.
-
-\item {\tt which.xs}: For quantitle-quantile plots, specifies particular covariate names in a
- character vector to plot only a subset of the covariates.
-
-\item {\tt subclass}: If \texttt{interactive = FALSE}, users can
- specify which subclass to plot.
-
-\end{itemize}
-
-\subsubsection{Output Values}
-
-\begin{itemize}
-\item Empirical quantile-quantile plot: This graph plots covariate
- values that fall in (approximately) the same quantile of treated and
- control distributions. Control unit quantile values are plotted on
- the x-axis, and treated unit quantile values are plotted on the
- y-axis. If values fall below the 45 degree line, control units
- generally take lower values of the covariate. Data points that fall
- exactly on the 45 degree line indicate that the marginal
- distributions are identical.
-
-\item Jitter plots: This graph plots jittered estimated propensity
- scores of treated and control units. Dark diamonds indicate matched
- units and grey diamonds indicate unmatched or discarded units. The
- area of the diamond is proportional to the weights. Vertical lines
- are plotted if subclassification is used.
-
-\item Histograms: This graph plots histograms of the estimated propensity
-scores in the original treated and control groups and weighted histograms of the estimated
-propensity scores in the matched treated and control groups. Plots can be compared vertically to
-quickly check the balance before and after matching.
-
-\end{itemize}
-
-\subsection{Plot options for the matchit summary object}
-You can also send a matchit summary object to the \texttt{plot()} command, to obtain
-a summary of the balance on each covariate before and after matching. The summary() object
-must have been created using the option \texttt{standardize=TRUE}. The idea for this plot
-came from the ``twang" package by McCaffrey, Ridgeway, and Morral.
-
-\subsubsection{Syntax}
-
-\begin{verbatim}
-> s.out <- summary(object, standardize=TRUE, ...)
-
-> plot(s.out, ...)
-\end{verbatim}
-
-\subsubsection{Arguments}
-
-\begin{itemize}
-\item {\tt interactive}: If \texttt{TRUE} (default), users can
- identify individual variables by clicking on the graph with the left
- mouse button.
-\end{itemize}
-
-\subsubsection{Output Values}
-
-\begin{itemize}
-\item Line plot of standardized differences in means before and after matching.
-Numbers plotted are those output by the summary() command in the sum.all and sum.matched
-objects.
-\end{itemize}
-
-
-
-%%% Local Variables:
-%%% mode: latex
-%%% TeX-master: "matchit"
-%%% End:
-
diff --git a/vignettes/preprocess.tex b/vignettes/preprocess.tex
deleted file mode 100644
index 1023b0d..0000000
--- a/vignettes/preprocess.tex
+++ /dev/null
@@ -1,233 +0,0 @@
-\section{Preprocessing via Matching}
-\label{sec:matching}
-
-\subsection{Quick Overview}
-
-The main command \texttt{matchit()} implements the matching
-procedures. A general syntax is:
-\begin{verbatim}
-> m.out <- matchit(treat ~ x1 + x2, data = mydata)
-\end{verbatim}
-where {\tt treat} is the dichotomous treatment variable, and {\tt x1}
-and {\tt x2} are pre-treatment covariates, all of which are contained
-in the data frame {\tt mydata}. The dependent variable (or variables)
-may be included in \texttt{mydata} for convenience but is never used
-by \MatchIt\ or included in the formula. This command creates the
-\MatchIt\ object called \texttt{m.out}. Name the output object to see
-a quick summary of the results:
-\begin{verbatim}
-> m.out
-\end{verbatim}
-
-\subsection{Examples}
-
-To run any of the examples below, you first must load the library and
-and data:
-\begin{verbatim}
-> library(MatchIt)
-> data(lalonde)
-\end{verbatim}
-
-Our example data set is a subset of the job training program analyzed
-in \citet{lalonde86} and \citet{DehWah99}. \MatchIt\ includes a
-subsample of the original data consisting of the National Supported
-Work Demonstration (NSW) treated group and the comparison sample from
-the Population Survey of Income Dynamics (PSID).\footnote{This data
- set, \texttt{lalonde}, was created using NSWRE74$\_$TREATED.TXT and
- CPS3$\_$CONTROLS.TXT from
- http://www.columbia.edu/$\sim$rd247/nswdata.} The variables in this
-data set include participation in the job training program
-(\texttt{treat}, which is equal to 1 if participated in the program,
-and 0 otherwise), age ({\tt age}), years of education ({\tt educ}),
-race (\texttt{black} which is equal to 1 if black, and 0 otherwise;
-\texttt{hispan} which is equal to 1 if hispanic, and 0 otherwise),
-marital status (\texttt{married}, which is equal to 1 if married, 0
-otherwise), high school degree (\texttt{nodegree}, which is equal to 1
-if no degree, 0 otherwise), 1974 real earnings (\texttt{re74}), 1975
-real earnings (\texttt{re75}), and the main outcome variable, 1978
-real earnings (\texttt{re78}).
-
-\subsubsection{Exact Matching}
-\label{subsubsec:exact}
-
-The simplest version of matching is exact. This technique matches
-\emph{each} treated unit to \emph{all} possible control units with
-exactly the same values on all the covariates, forming subclasses such
-that within each subclass all units (treatment and control) have the
-same covariate values. Exact matching is implemented in \MatchIt\
-using \texttt{method = "exact"}. Exact matching will be done on all
-covariates included on the right-hand side of the \texttt{formula}
-specified in the \MatchIt\ call. There are no additional options for
-exact matching. (Exact restrictions on a subset of covariates can
-also be specified in nearest neighbor matching; see
-Section~\ref{subsubsec:nearest}.) The following example can be
-run by typing {\tt demo(exact)} at the R prompt,
-\begin{verbatim}
-> m.out <- matchit(treat ~ educ + black + hispan, data = lalonde,
- method = "exact")
-\end{verbatim}
-
-\subsubsection{Subclassification}
-\label{subsubsec:subclass}
-
-When there are many covariates (or some covariates can take a large
-number of values), finding sufficient exact matches will often be
-impossible. The goal of subclassification is to form subclasses, such
-that in each the distribution (rather than the exact values) of
-covariates for the treated and control groups are as similar as
-possible. Various subclassification schemes exist, including the one
-based on a scalar distance measure such as the propensity score
-estimated using the \texttt{distance} option (see
-Section~\ref{subsubsec:inputs-all}). Subclassification is implemented
-in \MatchIt\ using \texttt{method = "subclass"}.
-
-The following example script can be run by typing {\tt demo(subclass)}
-at the R prompt,
-\begin{verbatim}
-> m.out <- matchit(treat ~ re74 + re75 + educ + black + hispan + age,
- data = lalonde, method = "subclass")
-\end{verbatim}
-The above syntax forms 6 subclasses, which is the default number
-of subclasses, based on a distance measure (the propensity score) estimated using logistic
-regression. By default, each subclass will have approximately the
-same number of treated units.
-
-Subclassification may also be used in conjunction with nearest
-neighbor matching described below, by leaving the default of
-\texttt{method = "nearest"} but adding the option \texttt{subclass}.
-When you choose this option, \MatchIt\ selects matches using nearest neighbor
-matching, but
-after the nearest neighbor matches are chosen it places them into
-subclasses, and adds a variable to the output object indicating subclass membership.
-
-
-\subsubsection{Nearest Neighbor Matching}
-\label{subsubsec:nearest}
-
-Nearest neighbor matching selects the $r$ (default=1) best control
-matches for each individual in the treatment group (excluding those
-discarded using the \texttt{discard} option). Matching is done
-using a distance measure specified by the {\tt distance} option
-(default=logit). Matches are chosen for each treated unit one at a
-time, with the order specified by the \texttt{m.order} command (default=largest to smallest).
-At each matching step we choose the control unit that is not
-yet matched but is closest to the treated unit on the distance
-measure.
-
-Nearest neighbor matching is implemented in \MatchIt\ using the
-\texttt{method = "nearest"} option. The following example script can
-be run by typing {\tt demo(nearest)}:
-\begin{verbatim}
-> m.out <- matchit(treat ~ re74 + re75 + educ + black + hispan + age,
- data = lalonde, method = "nearest")
-\end{verbatim}
-
-\subsubsection{Optimal Matching}
-\label{subsubsec:optimal}
-
-The default nearest neighbor matching method in \MatchIt\ is
-``greedy'' matching, where the closest control match for each treated
-unit is chosen one at a time, without trying to minimize a global
-distance measure. In contrast, ``optimal'' matching finds the matched
-samples with the smallest average absolute distance across all the
-matched pairs. \citet{GuRos93} find that greedy and optimal matching
-approaches generally choose the same sets of controls for the overall
-matched samples, but optimal matching does a better job of minimizing
-the distance within each pair. In addition, optimal matching can be
-helpful when there are not many appropriate control matches for the
-treated units.
-
-Optimal matching is performed with \MatchIt\ by setting \texttt{method
- = "optimal"}, which automatically loads an add-on package called
-\texttt{optmatch} \citep{Hansen04}. The following example can also be
-run by typing {\tt demo(optimal)} at the R prompt. We conduct 2:1 optimal
-ratio matching based on the propensity score from the logistic
-regression.
-\begin{verbatim}
-> m.out <- matchit(treat ~ re74 + re75 + age + educ, data = lalonde,
- method = "optimal", ratio = 2)
-\end{verbatim}
-
-\subsubsection{Full Matching}
-\label{subsubsec:full}
-
-Full matching is a particular type of subclassification that forms the
-subclasses in an optimal way \citep{Rosenbaum02, Hansen04}. A fully
-matched sample is composed of matched sets, where each matched set
-contains one treated unit and one or more controls (or one control
-unit and one or more treated units). As with subclassification, the
-only units not placed into a subclass will be those discarded (if a
-\texttt{discard} option is specified) because they are outside the
-range of common support. Full matching is optimal in terms of
-minimizing a weighted average of the estimated distance measure
-between each treated subject and each control subject within each
-subclass.
-
-Full matching can be performed with \MatchIt\ by setting
-\texttt{method = "full"}. Just as with optimal matching, we use the
-\texttt{optmatch} package \citep{Hansen04}, which automatically loads
-when needed. The following example with full matching (using the
-default propensity score based on logistic regression) can also be run
-by typing {\tt demo(full)} at the R prompt:
-\begin{verbatim}
-> m.out <- matchit(treat ~ age + educ + black + hispan + married +
- nodegree + re74 + re75, data = lalonde, method = "full")
-\end{verbatim}
-
-\subsubsection{Genetic Matching}
-\label{subsub:genetic}
-
-Genetic matching automates the process of finding a good matching
-solution \citep{DiaSek05}. The idea is to use a genetic search
-algorithm to find a set of weights for each covariate such that the a
-version of optimal balance is achieved after matching. As currently
-implemented, matching is done with replacement using the matching
-method of \citet{AbaImb07} and balance is determined by two univariate
-tests, paired t-tests for dichotomous variables and a
-Kolmogorov-Smirnov test for multinomial and continuous variables, but
-these options can be changed.
-
-Genetic matching can be performed with \MatchIt\ by setting
-\texttt{method = "genetic"}, which automatically loads the
-\texttt{Matching} \citep{Sekhon04} package. The following example of
-genetic matching (using the estimated propensity score based on
-logistic regression as one of the covariates) can also be run by
-typing {\tt demo(genetic)}:
-\begin{verbatim}
-> m.out <- matchit(treat ~ age + educ + black + hispan + married + nodegree +
- re74 + re75, data = lalonde, method = "genetic")
-\end{verbatim}
-
-
-\subsubsection{Coarsened Exact Matching}
-\label{subsub:cem}
-
-Coarsened Exact Matching (CEM) is a Monotonoic Imbalance Bounding
-(MIB) matching method --- which means that the balance between the
-treated and control groups is chosen by the user ex ante rather than
-discovered through the usual laborious process of checking after the
-fact and repeatedly reestimating, and so that adjusting the imbalance
-on one variable has no effect on the maximum imbalance of any other.
-CEM also strictly bounds through ex ante user choice both the degree
-of model dependence and the average treatment effect estimation error,
-eliminates the need for a separate procedure to restrict data to
-common empirical support, meets the congruence principle, is robust to
-measurement error, works well with multiple imputation methods for
-missing data, and is extremely fast computationally even with very
-large data sets. CEM also works well for multicategory treatments,
-determining blocks in experimental designs, and evaluating extreme
-counterfactuals \citep{IacKinPor08}.
-
-CEM can be performed with \MatchIt\ by setting \texttt{method =
- "cem"}, which automatically loads the \texttt{cem} package. The
-following examples of CEM (with automatic coarsening) can also be run
-by typing \texttt{demo(cem)}:
-\begin{verbatim}
-m.out <- matchit(treat ~ age + educ + black + hispan + married + nodegree
- + re74 + re75, data = lalonde, method = "cem")
-\end{verbatim}
-
-%%% Local Variables:
-%%% mode: latex
-%%% TeX-master: "matchit"
-%%% End:
diff --git a/vignettes/summaryref.tex b/vignettes/summaryref.tex
deleted file mode 100644
index 7b8be8f..0000000
--- a/vignettes/summaryref.tex
+++ /dev/null
@@ -1,127 +0,0 @@
-\section{\texttt{summary()}: Numerical Summaries of Balance}
-
-The \texttt{summary()} command returns numerical summaries of balance
-diagnostics.
-
-\subsubsection{Syntax}
-\begin{verbatim}
-summary(object, interactions = FALSE, addlvariables = NULL, standardize = FALSE, ...)
-\end{verbatim}
-
-\subsubsection{Arguments}
-
-\begin{itemize}
-\item \texttt{object}: the output from {\tt matchit()}.
-\item \texttt{interactions}: an option to calculate summary statistics
- in \texttt{sum.all} and \texttt{sum.matched} for all covariates,
- their squares, and two-way interactions when \texttt{interactions =
- TRUE} and only the covariates themselves when \texttt{interactions
- = FALSE}, (DEFAULT = {\tt FALSE}).
-\item \texttt{addlvariables}: additional variables on which to
- calculate the diagnostic statistics (in addition to the variables
- included in the matching procedure) (DEFAULT = {\tt NULL}).
- \texttt{addlvariables}: a data frame containing additional variables
- whose balance is examined. The data should come with the same number
- of units and units in the same order as in the data set used for
- {\tt matchit()}.
-\item \texttt{standardize}: a logical variable indicating whether to
- standardize balance measures, i.e., whether the difference in means should be divided
- by the standard deviation in the original treated group. (DEFAULT = {\tt FALSE})
-\end{itemize}
-
-\subsubsection{Output Values}
-
-The output from the \texttt{summary()} command includes the following
-elements, when applicable:
-\begin{itemize}
-\item The original assignment model call.
-\item \texttt{sum.all}: a data frame that contains variable names and
- interactions down the row names, and summary statistics on \emph{all
- observations} in each of the columns. The columns in
- \texttt{sum.all} contain:
-%\footnote{The output for full matching is
-% slightly different from that described here; see Section
-% \ref{subsubsec:full} for details.}
- \begin{itemize}
- \item means of all covariates $X$ for treated and control units,
- where \texttt{Means Treated}$= \mu_{X|T=1} = \frac{1}{n_1}
- \sum_{T=1} X_i$ and \texttt{Means Control}$= \mu_{X|T=0} =
- \frac{1}{n_0} \sum_{T=0} X_i$,
- \item standard deviation in the control group for all covariates $X$, where applicable,
- $$\quad s_{x|T=0} = \sqrt{\frac{\sum_{i \in \{i: T_i=0\}}
- (X_i - \mu_{X|T=0})^2}{n_0-1} }.$$
- \item balance statistics of the original data (before matching),
- which compare treated and control covariate distributions. If {\tt
- standardize = FALSE}, balance measures will be presented on the
- original scale. Specifically, mean differences (\texttt{Mean
- Diff.}) as well as the median, mean, and maximum value of
- differences in empirical quantile functions for each covariate
- will be given (\texttt{eQQ Med}, \texttt{eQQ Mean}, and
- \texttt{eQQ Max}, respectively). If {\tt standardize = TRUE}, the
- balance measures will be standardized. Standardized mean
- differences (\texttt{Std.\ Mean Diff.}), defined as
- $\frac{\mu_{X|T=1} - \mu_{X|T=0}}{s_{x|T=1}}$, as well as the
- median, mean, and maximum value of differences in empirical
- cumulative distribution functions for each covariate will be given
- (\texttt{eCDF Med}, \texttt{eCDF Mean}, and \texttt{eCDF Max},
- respectively).
- \end{itemize}
-
-\item \texttt{sum.matched}: a data frame which contains variable names
- down the row names, and summary statistics on only the \emph{matched
- observations} in each of the columns. Specifically, the columns
- in \texttt{sum.matched} contain the following elements:
-%\footnote{The
-% values output for full matching are slightly different from that
-% described here; see Section \ref{subsubsec:full} for details}:
- \begin{itemize}
- \item weighted means for matched treatment units and matched control units of all covariates
- $X$ and their interactions, where \texttt{Means Treated}$=
- \mu_{wX|T=1} = \frac{1}{n_1} \sum_{T=1} w_iX_i$ and \texttt{Means
- Control}$=\mu_{wX|T=0} = \frac{1}{n_0} \sum_{T=0} w_iX_i$,
- \item weighted standard deviations in the matched control group for
- all covariates $X$, where applicable, where \texttt{SD} $= s_{wX} =
- \sqrt{\frac{1}{n} \sum_{i} (w_iX_i - \overline{X}^*)^2}$, where
- $\overline{X}^*$ is the weighted mean of $X$ in the matched
- control group, and
- \item balance statistics of the matched data (after matching), which
- compare treated and control covariate distributions. If {\tt
- standardize = FALSE}, balance measures will be presented on the
- original scale. Specifically, mean differences (\texttt{Mean
- Diff.}) as well as the median, mean, and maximum value of
- differences in empirical quantile functions for each covariate
- will be given (\texttt{eQQ Med}, \texttt{eQQ Mean}, and
- \texttt{eQQ Max}, respectively). If {\tt standardize = TRUE}, the
- balance measures will be standardized. Standardized mean
- differences (\texttt{Std.\ Mean Diff.}), defined as
- $\frac{\mu_{wX|T=1} - \mu_{wX|T=0}}{s_{x|T=1}}$, as well as the
- median, mean, and maximum value of differences in empirical
- cumulative distribution functions for each covariate will be given
- (\texttt{eCDF Med}, \texttt{eCDF Mean}, and \texttt{eCDF Max},
- respectively).
- \end{itemize}
- where $w$ represents the vector of \texttt{weights}.
-
-\item \texttt{reduction}: the percent reduction in the difference in
- means achieved in each of the balance measures in \texttt{sum.all}
- and \texttt{sum.matched}, defined as $100(|a|-|b|)/|a|$, where $a$
- was the value of the balance measure before matching and $b$ is the
- value of the balance measure after matching.
-
-\item \texttt{nn}: the sample sizes in the full and matched samples
- and the number of discarded units, by treatment and control.
-
-\item \texttt{q.table}: an array that contains the same information
- as \texttt{sum.matched} by subclass.
-
-\item \texttt{qn}: the sample sizes in the full and matched
- samples and the number of discarded units, by subclass and by
- treatment and control.
-\item \texttt{match.matrix}: the same object is contained in the
- output of {\tt matchit()}.
-\end{itemize}
-
-%%% Local Variables:
-%%% mode: latex
-%%% TeX-master: "matchit"
-%%% End:
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