[r-cran-erm] 13/33: Import Upstream version 0.13-4.1~svn66
Andreas Tille
tille at debian.org
Mon Dec 12 11:19:33 UTC 2016
This is an automated email from the git hooks/post-receive script.
tille pushed a commit to branch master
in repository r-cran-erm.
commit 81ae53d781f2c1aab40d2170a95e3c15609032d7
Author: Andreas Tille <tille at debian.org>
Date: Mon Dec 12 11:20:02 2016 +0100
Import Upstream version 0.13-4.1~svn66
---
DESCRIPTION | 52 +-
NAMESPACE | 1 +
NEWS | 43 +-
R/LRtest.Rm.R | 7 +-
R/MLoef.R | 141 +-
R/NPtest.R | 12 +
R/Rsquared.R | 0
R/Waldtest.Rm.R | 3 +-
R/cldeviance.R | 0
R/datcheck.R | 46 +-
R/gofIRT.R | 0
R/gofIRT.ppar.R | 0
R/hoslem.R | 0
R/{itemfit.ppar.r => itemfit.ppar.R} | 0
R/plotDIF.R | 164 +
R/plotICC.Rm.R | 5 +-
R/plotPWmap.R | 59 +-
R/predict.ppar.R | 0
R/print.gof.R | 0
R/{print.logLik.eRm.r => print.logLik.eRm.R} | 0
R/rostdeviance.r | 0
R/summary.MLoef.r | 36 +-
R/summary.gof.R | 0
R/zzz.R | 13 -
inst/doc/Rplots.pdf | 4482 ++++++++++++++++++++++++++
inst/doc/eRm.R | 0
inst/doc/eRm.Rnw | 0
inst/doc/eRm.pdf | Bin 694121 -> 555998 bytes
inst/doc/{eRm.R => eRmvig.R} | 0
inst/doc/{eRm.Rnw => eRmvig.Rnw} | 0
inst/doc/eRmvig.bib | 108 +-
inst/doc/eRmvig.pdf | Bin 0 -> 433168 bytes
man/MLoef.Rd | 34 +-
man/eRm-package.Rd | 7 +-
man/plotDIF.Rd | 114 +
man/plotPWmap.Rd | 16 +-
36 files changed, 5102 insertions(+), 241 deletions(-)
diff --git a/DESCRIPTION b/DESCRIPTION
index a9225c4..5ae1f87 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,28 +1,24 @@
-Package: eRm
-Type: Package
-Title: Extended Rasch Modeling.
-Version: 0.13-0
-Date: 2010-06-12
-Author: Patrick Mair, Reinhold Hatzinger, Marco Maier
-Maintainer: Patrick Mair <patrick.mair at wu.ac.at>
-Description: eRm fits Rasch models (RM), linear logistic test models
- (LLTM), rating scale model (RSM), linear rating scale models
- (LRSM), partial credit models (PCM), and linear partial credit
- models (LPCM). Missing values are allowed in the data matrix.
- Additional features are the ML estimation of the person
- parameters, Andersen's LR-test, item-specific Wald test,
- Martin-Loef-Test, nonparametric Monte-Carlo Tests, itemfit and
- personfit statistics including infit and outfit measures,
- various ICC and related plots, automated stepwise item
- elimination, simulation module for various binary data
- matrices. An eRm platform is provided at R-forge (see URL).
-License: GPL
-Encoding: latin1
-URL: http://r-forge.r-project.org/projects/erm/
-Imports: graphics, stats, MASS, methods
-Depends: R (>= 2.9.0), splines, methods, RaschSampler
-LazyData: yes
-LazyLoad: yes
-Packaged: 2010-06-12 08:52:24 UTC; mair
-Repository: CRAN
-Date/Publication: 2010-06-14 07:05:20
+Package: eRm
+Type: Package
+Title: Extended Rasch Modeling.
+Version: 0.13-4
+Date: 2011-03-23
+Author: Patrick Mair, Reinhold Hatzinger, Marco Maier
+Maintainer: Patrick Mair <patrick.mair at wu.ac.at>
+Description: eRm fits Rasch models (RM), linear logistic test models
+ (LLTM), rating scale model (RSM), linear rating scale models
+ (LRSM), partial credit models (PCM), and linear partial credit
+ models (LPCM). Missing values are allowed in the data matrix.
+ Additional features are the ML estimation of the person
+ parameters, Andersen's LR-test, item-specific Wald test,
+ Martin-Loef-Test, nonparametric Monte-Carlo Tests,
+ itemfit and personfit statistics including infit and outfit
+ measures, various ICC and related plots, automated stepwise
+ item elimination, simulation module for various binary data
+ matrices. An eRm platform is provided at R-forge (see URL).
+License: GPL
+URL: http://r-forge.r-project.org/projects/erm/
+Imports: graphics, stats, MASS, methods
+Depends: R (>= 2.12.0), splines, methods, RaschSampler
+LazyData: yes
+LazyLoad: yes
diff --git a/NAMESPACE b/NAMESPACE
index 4f4695a..cccc505 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -11,6 +11,7 @@ export(MLoef)
export(itemfit)
export(person.parameter)
export(personfit)
+export(plotDIF)
export(plotGOF)
export(plotICC)
export(plotjointICC)
diff --git a/NEWS b/NEWS
index 58440ef..c1f3c5c 100644
--- a/NEWS
+++ b/NEWS
@@ -1,6 +1,45 @@
+Changes in Version 0.13-4
+
+ o new function plotDIF (by Kathrin Gruber): plots confidence
+ intervals for item parameters estimated separately in
+ subgroups, uses LR objects as input
+
+ o adapted the MLoef function to work with polytomous data
+
+Changes in Version 0.13-3
+
+ o error checks in NPtest: (i) 0/full resposes for items
+ meaningless for NPtest, (ii) group in method="T4" must
+ be of type logical, (iii) specifying all items for
+ T4 gives meaningless results.
+
+ o warning regarding group assignment when using median
+ split removed from LRtest and Waldtest
+
+Changes in Version 0.13-2
+
+ o some modifications in plotPWmap: horizontal plotting,
+ different default plotting symbols, option to change
+ size of plotting symbols
+
+ o bug in MLoef fixed (now using logs in calculating the
+ person contributions)
+
+ o eRm now depends on R >= 2.12.0
+
+ o Latin1 encoding removed
+
+
+Changes in Version 0.13-1
+
+ o bug in plotICC (always same title) fixed
+
Changes in Version 0.13-0
- o LLTM, LRSM, and LPCM work now for repeated measurement designs with treatment groups and missing values.
- o Rename vignette to 'eRm'.
+
+ o LLTM, LRSM, and LPCM work now for repeated measurement
+ designs with treatment groups and missing values.
+
+ o Rename vignette to 'eRm'.
Changes in Version 0.12-2
diff --git a/R/LRtest.Rm.R b/R/LRtest.Rm.R
index 3e83f56..7d62e31 100644
--- a/R/LRtest.Rm.R
+++ b/R/LRtest.Rm.R
@@ -75,7 +75,8 @@ if (!is.numeric(splitcr)) {
if (splitcr=="median") { #median split
spl.gr<-c("Raw Scores <= Median", "Raw Scores > Median")
- cat("Warning message: Persons with median raw scores are assigned to the lower raw score group!\n")
+ #removed rh 2010-12-17
+ #cat("Warning message: Persons with median raw scores are assigned to the lower raw score group!\n")
rv <- apply(object$X,1,sum,na.rm=TRUE)
rvsplit <- median(rv)
rvind <- rep(0,length(rv))
@@ -134,7 +135,7 @@ if (length(del.pos) > 0) {
}
Xlist.n <- by(X.el,rvind,function(y) y)
names(Xlist.n) <- names(Xlist)
-if (length(del.pos) > 0) Xlist.n <- c(Xlist.n,list(X.el))
+if (length(del.pos) > 0) Xlist.n <- c(Xlist.n,list(X.el)) # X.el added since we must refit whole group without del.pos items
if (object$model=="RM") {
likpar <- sapply(Xlist.n,function(x) { #matrix with loglik and npar for each subgroup
@@ -166,7 +167,7 @@ if (object$model=="RSM") {
}
## extract fitted splitgroup models # rh 02-05-2010
-fitobj<-likpar[6,]
+fitobj<-likpar[6,1:length(unique(rvind))]
likpar<-likpar[-6,]
if (length(del.pos) > 0) { #re-estimate full model
diff --git a/R/MLoef.R b/R/MLoef.R
index 0349ee6..98a1a3b 100644
--- a/R/MLoef.R
+++ b/R/MLoef.R
@@ -1,6 +1,6 @@
MLoef <- function(robj, splitcr="median")
{
-# performs the Martin-L�f LR-test
+# performs the Martin-Loef LR-test
# robj... object of class RM
# splitcr... splitting criterion for two groups. "median" (default) and "mean"
# split items in two groups according to the median/mean or item raw
@@ -8,13 +8,14 @@ MLoef <- function(robj, splitcr="median")
# a vector of length k (number of items) containing two different
# elements signifying group membership of items can be supplied.
- if(all(class(robj) != "Rm")) stop("robj must be of class \"Rm\".")
+ ### no test with missing values rh 19-05-10
+ if(any(is.na(robj$X))) stop("Martin-Loef Test with NA currently not available\n")
wrning <- NULL # initialize an object for warnings
if(length(splitcr) == 1){ # generate split-vector if "mean" or "median"
- if(splitcr=="median"){
- raw.scores <- colSums(robj$X01,na.rm=T)
+ if(splitcr == "median"){
+ raw.scores <- colSums(robj$X,na.rm=T)
numsplit <- as.numeric(raw.scores > median(raw.scores,na.rm=T))
if( any(raw.scores == median(raw.scores,na.rm=T)) ){ # Only if one item's raw score == the median, a warning is issued
wrning <- which(raw.scores == median(raw.scores,na.rm=T)) # append a warning-slot to the object for print and summary methods
@@ -22,83 +23,109 @@ MLoef <- function(robj, splitcr="median")
}
}
if(splitcr=="mean"){
- raw.scores <- colSums(robj$X01,na.rm=T)
+ raw.scores <- colSums(robj$X,na.rm=T)
numsplit <- as.numeric(raw.scores > mean(raw.scores,na.rm=T))
if( any(raw.scores == mean(raw.scores,na.rm=T)) ){ # Only if one item's raw score == the mean, a warning is issued
wrning <- which(raw.scores == mean(raw.scores,na.rm=T)) # append a warning-slot to the object for print and summary methods
cat("Item(s)",paste(names(wrning),collapse=", "),"with raw score equal to the mean assigned to the lower raw score group!\n")
}
}
- }
- else{ # check if the submitted split-vector is appropriate
- if(length(splitcr) != ncol(robj$X01)) stop("Split vector too long/short.")
- if(length(unique(splitcr)) > 2) stop("Only two groups allowed.")
- if(length(unique(splitcr)) < 2) stop("Split vector must contain two groups.")
+ } else { # check if the submitted split-vector is appropriate
+ if(length(splitcr) != ncol(robj$X)) stop("Split vector too long/short.")
+# if(length(unique(splitcr)) > 2) stop("Only two groups allowed.")
+ if(length(unique(splitcr)) < 2) stop("Split vector must contain at least two groups.")
numsplit <- splitcr
}
sp.groups <- unique(numsplit)
- i.groups <- list(which(numsplit == sp.groups[1]), which(numsplit == sp.groups[2]))
+ i.groups <- sapply(sp.groups, function(g){ which(numsplit == g) }, simplify=F)
- # check if one group countains less than 2 items
- if( (length(i.groups[[1]]) < 2) | (length(i.groups[[2]]) < 2) ){
+ # check if any group countains less than 2 items
+ if( any(unlist(lapply(i.groups, length)) < 2) ){
stop("Each group of items must contain at least 2 items.")
}
# check if one group contains subject with <=1 valid responses
- if(any(rowSums(is.na(robj$X01[,i.groups[[1]]])) >= (length(i.groups[[1]]) - 1)))stop("Group 1 contains subjects with less than two valid responses.")
- if(any(rowSums(is.na(robj$X01[,i.groups[[2]]])) >= (length(i.groups[[2]]) - 1)))stop("Group 2 contains subjects with less than two valid responses.")
-
- ### no test with missing values rh 19-05-10
- if (any(is.na(robj$X)))stop("Martin-Loef Test with NA currently not available\n")
+ if(any(unlist(lapply(i.groups, function(g){ any(rowSums(!is.na(robj$X[,g])) <= 1) })))) stop("Groups contain subjects with less than two valid responses.")
### possible missing patterns and classification of persons into groups
- MV.X <- apply(matrix(as.numeric(is.na(robj$X01)),ncol=ncol(robj$X01)),1,paste,collapse="")
- MV.p <- sort(unique(MV.X))
- MV.g <- numeric(length=length(MV.X))
- g <- 1
- for(i in MV.p){
- MV.g[MV.X == i] <- g;
- g <- g + 1
- }
- na.X01 <- list()
- for(i in 1:length(MV.p)){
- na.X01[[i]] <- matrix(robj$X01[which(MV.g == i),], ncol=ncol(robj$X01))
- }
+# MV.X <- apply(matrix(as.numeric(is.na(robj$X01)),ncol=ncol(robj$X01)),1,paste,collapse="")
+# MV.p <- sort(unique(MV.X))
+# MV.g <- numeric(length=length(MV.X))
+# g <- 1
+# for(i in MV.p){
+# MV.g[MV.X == i] <- g;
+# g <- g + 1
+# }
+# na.X01 <- list()
+# for(i in 1:length(MV.p)){
+# na.X01[[i]] <- matrix(robj$X01[which(MV.g == i),], ncol=ncol(robj$X01))
+# }
+
+# res1 <- RM(robj$X01[,i.groups[[1]]])
+# res2 <- RM(robj$X01[,i.groups[[2]]])
- res1 <- RM(robj$X01[,i.groups[[1]]])
- res2 <- RM(robj$X01[,i.groups[[2]]])
+ # fitting the submodels
+ subModels <- lapply(i.groups, function(g){ PCM(robj$X[,g]) })
### calculating the numerator and denominator
- ml.num <- ml.den <- numeric()
+ sub.tabs <- as.data.frame(sapply(subModels, function(M){
+ rowSums(M$X, na.rm=T)
+ }))
+ sub.tabs <- table(sub.tabs)
+
+ sub.term <- sub.tabs * (log(sub.tabs) - log(nrow(robj$X)))
+ sub.term <- sum(na.omit(as.numeric(sub.term)))
+
+ sub.max <- lapply(i.groups, function(g){ sum(apply(robj$X[,g], 2, max)) })
+
+ full.tab <- table(rowSums(robj$X, na.rm=T))
+ full.term <- sum(na.omit(as.numeric( full.tab * (log(full.tab) - log(nrow(robj$X))) )))
- for(i in 1:length(MV.p)){
- .temp.num <- table(rowSums(na.X01[[i]],na.rm=T))
- ml.num[i] <- sum(log((.temp.num/sum(.temp.num))^.temp.num))
+ ML.LR <- 2 * (
+ sub.term + sum(unlist(lapply(subModels, `[[`, "loglik")))
+ - full.term - robj$loglik
+ )
- if(nrow(na.X01[[i]]) > 1){
- .temp.den <- table(rowSums(na.X01[[i]][,i.groups[[1]]],na.rm=T),
- rowSums(na.X01[[i]][,i.groups[[2]]],na.rm=T))
- }
- else{
- .temp.den <- table(sum(na.X01[[i]][,i.groups[[1]]],na.rm=T),
- sum(na.X01[[i]][,i.groups[[2]]],na.rm=T))
- }
- ml.den[i] <- sum(log((.temp.den/sum(.temp.den))^.temp.den))
- }
+ df <- prod(unlist(sub.max)+1) - (sum(apply(robj$X, 2, max))+1) - length(sp.groups) + 1
- a <- sum(ml.num)
- b <- sum(ml.den)
- k <- c(length(i.groups[[1]]),length(i.groups[[2]]))
+# ml.num <- ml.den <- df <- numeric()
- ML.LR <- -2*( (a + robj$loglik) - (b + res1$loglik + res2$loglik) )
- DF <- prod(k) - 1
- p.value <- 1 - pchisq(ML.LR, DF)
+# for(i in 1:length(MV.p)){
+# .temp.num <- table(rowSums(na.X01[[i]],na.rm=T))
+# .temp.num <- .temp.num[.temp.num > 0] ### rh
+# ml.num[i] <- sum( (log(.temp.num)-log(sum(.temp.num)))*.temp.num )
+#
+# if(nrow(na.X01[[i]]) > 1){
+# .temp.den <- table(rowSums(na.X01[[i]][,i.groups[[1]]],na.rm=T),
+# rowSums(na.X01[[i]][,i.groups[[2]]],na.rm=T))
+# }
+# else{
+# .temp.den <- table(sum(na.X01[[i]][,i.groups[[1]]],na.rm=T),
+# sum(na.X01[[i]][,i.groups[[2]]],na.rm=T))
+# }
+# .temp.den <- .temp.den[.temp.den > 0] ### rh
+# ml.den[i] <- sum( (log(.temp.den)-log(sum(.temp.den)))*.temp.den )
+#
+# k1 <- sum(!is.na(na.X01[[i]][1,i.groups[[1]]])) ### rh
+# k2 <- sum(!is.na(na.X01[[i]][1,i.groups[[2]]])) ### rh
+# df[i] <- k1 * k2 -1 ### rh
+# }
+#
+# a <- sum(ml.num)
+# b <- sum(ml.den)
+# k <- c(length(i.groups[[1]]),length(i.groups[[2]]))
+#
+# ML.LR <- -2*( (a + robj$loglik) - (b + res1$loglik + res2$loglik) )
+# DF <- prod(k) - 1
+ p.value <- 1 - pchisq(ML.LR, df)
- result <- list(X01=robj$X01, model=robj$model, LR=ML.LR,
- df=DF, p.value=p.value, L0=robj$loglik, L1=res1$loglik, L2=res2$loglik,
- theta.table.RM=table(rowSums(robj$X01)), # both used for the plotting
- theta.table.MLoef=table(rowSums(res1$X01),rowSums(res2$X01)), # routine plot.MLoef
- items1=i.groups[[1]], items2=i.groups[[2]], k=k,
+ result <- list(LR=ML.LR, df=df, p.value=p.value,
+ fullModel=robj, subModels=subModels,
+ Lf=robj$loglik, Ls=lapply(subModels, `[[`, "loglik"),
+# theta.table.RM=table(rowSums(robj$X01)), # both used for the plotting
+# theta.table.MLoef=table(rowSums(res1$X01),rowSums(res2$X01)), # routine plot.MLoef
+ i.groups=i.groups,
+# items1=i.groups[[1]], items2=i.groups[[2]], k=k,
splitcr=splitcr, split.vector=numsplit, warning=wrning, call=match.call())
class(result) <- "MLoef"
return(result)
diff --git a/R/NPtest.R b/R/NPtest.R
index 0a39d5e..6a7e4a2 100644
--- a/R/NPtest.R
+++ b/R/NPtest.R
@@ -2,6 +2,14 @@ NPtest<-function(obj, n=NULL, method="T1", ...){
if (is.matrix(obj) || is.data.frame(obj)){ # input is datamatrix - RaschSampler object is generated
if (!all(obj %in% 0:1)) stop("Data matrix must be binary, NAs not allowed")
+ itscor<-colSums(obj) # rh 2011-03-03
+ itcol<-(itscor==0|itscor==nrow(obj))
+ if (any(itcol)){
+ cat("The following columns in the data show complete 0/full responses: \n")
+ cat((1:ncol(obj))[itcol],sep=", ")
+ cat("\n")
+ stop("NPtest using these items is meaningless. Delete them first!")
+ }
if (is.null(n)) n <- 500
obj<-rsampler(obj,rsctrl(burn_in=256, n_eff=n, step=32))
}
@@ -81,8 +89,12 @@ T4<-function(rsobj,idx=NULL,group=NULL,alternative="high"){
k<-rsobj$k # number of items
if(is.null(idx))
stop("No item(s) for subscale specified (use idx!)")
+ if(length(idx)==k) # rh 2011-03-03
+ stop("Subscale containing all items gives meaningless results for T4.")
if(is.null(group))
stop("No group specified (use group!)")
+ if(!is.logical(group)) # added rh 2011-03-03
+ stop("group must be of type \"logical\" (e.g., group = (age==1) )")
if(alternative=="high")
sign <- 1
else if(alternative=="low")
diff --git a/R/Rsquared.R b/R/Rsquared.R
old mode 100644
new mode 100755
diff --git a/R/Waldtest.Rm.R b/R/Waldtest.Rm.R
index 73b7257..feb9cdd 100644
--- a/R/Waldtest.Rm.R
+++ b/R/Waldtest.Rm.R
@@ -44,7 +44,8 @@ if (any(is.na(object$X))) {
}
if (!numsplit && splitcr=="median") { #median split
spl.gr<-c("Raw Scores <= Median", "Raw Scores > Median")
- cat("Warning message: Persons with median raw scores are assigned to the lower raw score group!\n")
+ #removed rh 2010-12-17
+ #cat("Warning message: Persons with median raw scores are assigned to the lower raw score group!\n")
X<-object$X
# calculates index for NA groups
# from person.parameter.eRm
diff --git a/R/cldeviance.R b/R/cldeviance.R
old mode 100644
new mode 100755
diff --git a/R/datcheck.R b/R/datcheck.R
index 87d3044..925b8bc 100644
--- a/R/datcheck.R
+++ b/R/datcheck.R
@@ -2,34 +2,34 @@
function(X,W,mpoints,groupvec,model)
{
if (is.data.frame(X)) {X <- as.matrix(X)} #X as data frame allowed
-
+
if (is.null(colnames(X))) { #determine item names
if (mpoints > 1) {
mpind <- paste("t",rep(1:mpoints,each=(dim(X)[2]/mpoints),1),sep="") #time points
- itemind <- paste("I",1:(dim(X)[2]/mpoints),sep="")
+ itemind <- paste("I",1:(dim(X)[2]/mpoints),sep="")
colnames(X) <- paste(itemind,mpind)
- } else {
+ } else {
colnames(X) <- paste("I",1:dim(X)[2],sep="") #item labels
}}
if (is.null(rownames(X))) rownames(X) <- paste("P",1:dim(X)[1],sep="") #person labels
-
+
#----------------------- check groupvec --------------------------
-
+
if ((length(groupvec) > 1) && (length(groupvec) != dim(X)[1])) {
stop("Wrong specification of groupvec!")}
-
+
if (min(groupvec)!=1) {
stop("Group specification must start with 1!")}
-
+
if (length(unique(groupvec))!=(max(groupvec))) {
- stop("Group vector is specified wrongly!")}
-
+ stop("Group vector is incorrectly specified (perhaps a category is missing)!")} # rh 2011-03-03
+
if ((max(groupvec) > 1) && (mpoints==1)) {
stop("Model not identifiable! Group contrasts can only be imposed for repeated measurement designs.") }
-
+
# if ((length(groupvec) > 1) && any(is.na(X))) {
# stop("Model with repeated measures, group specification and NAs cannot be computed!") }
-
+
#----------------------- check X --------------------------------
allna.vec <- apply(X,2,function(y) {all(is.na(y))}) #eliminate items with all NA's
if (any(allna.vec)) {stop("There are items with full NA responses which must be deleted!")}
@@ -46,27 +46,27 @@ if (any(ri.min > 0)) {
cat(colnames(X)[ri.min>0],sep=", ")
cat("\n")
cat("Responses are shifted such that lowest category is 0. \n")
- cat("\n")
-}
+ cat("\n")
+}
X <- t(apply(X,1,function(y) {y-ri.min})) #shift down to 0
ri <- apply(X,2,sum,na.rm=TRUE) #item raw scores
n.NA <- colSums(apply(X,2,is.na)) #number of NA's per column
maxri <- (dim(X)[1]*(apply(X,2,max,na.rm=TRUE)))-n.NA #maximum item raw scores with NA
-TFcol <- ((ri==maxri) | (ri==0))
+TFcol <- ((ri==maxri) | (ri==0))
X.n <- X[,!TFcol] #new matrix with excluded items
item.ex <- (1:dim(X)[2])[TFcol] #excluded items
if (length(item.ex) > 0) {
if (mpoints == 1) {
cat("Warning message: The following items were excluded due to complete 0/full responses: \n")
cat(colnames(X)[item.ex],sep=", ")
- cat("\n")
+ cat("\n")
} else {
cat("The following items show complete 0/full responses: \n")
cat(colnames(X)[item.ex],sep=", ")
- cat("\n")
+ cat("\n")
stop("Estimation cannot be performed! Delete the correponding items for the other measurement points as well! \n")
-}}
+}}
if ((model=="PCM") || (model=="LPCM")) { #check if there are missing categories for PCM (for RSM doesn't matter)
tablist <- apply(X,2,function(x) list(as.vector(table(x))))
@@ -80,19 +80,19 @@ if ((model=="PCM") || (model=="LPCM")) { #check if there
cat("Warning message: Estimation may not be feasible. Please check data matrix! \n")
cat("\n")
}
-}
+}
#-------------------------- ill conditioned for RM and LLTM --------------
if ((model=="RM") || (model=="LLTM")) {
if (length(table(X.n)) != 2) stop("Dichotomous data matrix required!")
k.t <- dim(X.n)[2]/mpoints #check for each mpoint separately
- t.ind <- rep(1:mpoints,1,each=k.t)
+ t.ind <- rep(1:mpoints,1,each=k.t)
X.nlv <- split(t(X.n),t.ind) #split X due to mpoints
cn.lv <- split(colnames(X.n),t.ind)
X.nl <- lapply(X.nlv,matrix,ncol=k.t,byrow=TRUE)
for (i in 1:length(X.nl)) colnames(X.nl[[i]]) <- cn.lv[[i]]
-
+
for (l in 1:mpoints) { #check within mpoint
X.nll <- X.nl[[l]]
k <- ncol(X.nll)
@@ -110,10 +110,10 @@ if ((model=="RM") || (model=="LLTM")) {
n.suspcol <- colnames(X.nll)[suspcol]
cat("Suspicious items:",n.suspcol,"\n")
stop("Estimation stopped due to ill-conditioned data matrix X!")
- }
+ }
}}
-#----------------------- end ill-conditioned check -------------------------------
-
+#----------------------- end ill-conditioned check -------------------------------
+
list(X=X.n,groupvec=groupvec)
}
diff --git a/R/gofIRT.R b/R/gofIRT.R
old mode 100644
new mode 100755
diff --git a/R/gofIRT.ppar.R b/R/gofIRT.ppar.R
old mode 100644
new mode 100755
diff --git a/R/hoslem.R b/R/hoslem.R
old mode 100644
new mode 100755
diff --git a/R/itemfit.ppar.r b/R/itemfit.ppar.R
similarity index 100%
rename from R/itemfit.ppar.r
rename to R/itemfit.ppar.R
diff --git a/R/plotDIF.R b/R/plotDIF.R
new file mode 100644
index 0000000..7865b95
--- /dev/null
+++ b/R/plotDIF.R
@@ -0,0 +1,164 @@
+plotDIF <- function(object, item.subset=NULL, gamma = 0.95, main=NULL,
+ xlim=NULL, xlab=" ", ylab=" ", col=NULL, distance=10,
+ splitnames=NULL, leg=FALSE, legpos="bottomleft",...)
+{
+
+if(class(object)=="LR") ## added rh 11-03-17
+ object<-list(object)
+else if(is.list(object)) {
+ checklr <- sapply(object,class)
+ if (!all(checklr=="LR"))
+ stop("Elements of '",deparse(substitute(object)), "' must must be LRtest objects!")
+} else if(!is.list(object))
+ stop(deparse(substitute(object)), "must be a list of LRtest objects!")
+
+
+# extract number of LRtest objects
+M <- length(sapply(object, function(x) length(x)))
+
+# Confidence plot only for LRtest objects
+for(p in 1:M){
+ if((object[[p]]$model == "LLTM") || (object[[p]]$model == "LRSM") || (object[[p]]$model == "LPCM")){
+ stop("Confidence Plot is computed only for LRtest objects (RM, PCM, RSM)!")
+ } else
+ if(is.na(sum(unlist(object[[p]]$selist))) == TRUE){
+ stop("Confidence Plot is computed only for LRtest objects (RM) with standard errors (se=TRUE)!")
+ }
+}
+
+
+# confidences list for storing confints
+confidences1 <- vector("list")
+# for labeling list entries
+nam.lab <- vector("character")
+# subgroups splits
+n2 <- sapply(object, function(x) length(x$spl.gr))
+
+# loops for computing thresholds on LRtest objects
+ for(m in 1:M){
+ # confidences for dichotomous items
+ if(object[[m]]$model == "RM"){
+ confidences1[[m]] <- lapply(object[[m]]$fitobj,function(x){confint(x, level=gamma)})
+ } else {
+ # confidences for polytomous items
+ confidences1[[m]] <- lapply(object[[m]]$fitobj, function(x){confint(thresholds(x),level=gamma)})
+ }
+}
+
+
+if(is.null(names(object)) == TRUE){
+ names(confidences1) <- paste("LRtest", 1:M, sep="")
+} else {
+ names(confidences1) <- names(object)
+}
+confidences <- do.call(c,lapply(confidences1,function(x) x[1:length(x)]))
+
+model.vec <- vector("character")
+for(p in 1:M){
+model.vec[p] <- object[[p]]$model
+}
+ if(any(model.vec == "PCM") || any(model.vec == "RSM")){
+ model <- "PCM"
+ } else {
+ model <- "RM" }
+
+# extracting the longest element of confidences for definition of tickpositions and ticklabels
+# (snatches at the confidences-object index)
+factorlist <- (unique(unlist(lapply(confidences, function(x) dimnames(x)[[1]]))))
+#maxlist <- max(order(factorlist))
+
+ if(is.null(item.subset)){
+ if(model == "PCM"){
+ y.lab <- sub("thresh beta ", "", factorlist)
+ } else {
+ y.lab <- sub("beta ", "", factorlist)
+ }
+ } else
+ if(is.character(item.subset)){
+# item subset specified as character
+ if(model == "PCM"){
+ y.lab <- sub("(.+)[.][^.]+$", "\\1", sub("thresh beta ", "", factorlist)) # search only for a "." separation after item label
+ categ <- gsub("^.*\\.(.*)$","\\1", factorlist) # extract item categories - search only for a "." separation
+ y.lab.id <- y.lab %in% item.subset
+ y.lab1 <- y.lab[y.lab.id]
+ categ1 <- categ[y.lab.id]
+ y.lab <- paste(y.lab1, categ1, sep=".") # stick item categories and names together again
+ factorlist <- factorlist[y.lab.id]
+ } else {
+ y.lab <- sub("beta ", "", factorlist) # search only for a "." separation after item label
+ y.lab.id <- y.lab %in% item.subset
+ y.lab <- y.lab[y.lab.id]
+ factorlist <- factorlist[y.lab.id]
+ }
+ } else {
+# item subset specified as position number (index in data matrix)
+ if(model == "PCM"){
+ y.lab <- sub("(.+)[.][^.]+$", "\\1", sub("thresh beta ", "", factorlist)) # search only for a "." separation after item label
+ categ <- gsub("^.*\\.(.*)$","\\1", factorlist) # extract item categories - search only for a "." separation
+ y.lab2 <- unique(y.lab)[item.subset]
+ y.lab.id <- y.lab %in% y.lab2
+ y.lab1 <- y.lab[y.lab.id]
+ categ1 <- categ[y.lab.id]
+ y.lab <- paste(y.lab1, categ1, sep=".") # stick item categories and names together again
+ factorlist <- factorlist[y.lab.id]
+ } else {
+ y.lab <- sub("beta ", "", factorlist)
+ y.lab2 <- unique(y.lab)[item.subset]
+ y.lab.id <- y.lab %in% y.lab2
+ y.lab <- y.lab[y.lab.id]
+ factorlist <- factorlist[y.lab.id]
+ }
+}
+
+# setting range of xaxis
+if(is.null(xlim)==TRUE){
+ xlim <- range(unlist(confidences))
+}
+
+# setting tickpositions
+tickpos <- 1:(length(y.lab)) + 3.5/distance
+lty <- unlist(lapply(n2, function(i)1:i))
+
+# defining the plot
+if(is.null(main)) {
+ main<-paste("Confidence plot")
+}
+plot(xlim, xlim=xlim, ylim=c(length(y.lab) + 1.25,0.5), type="n", yaxt="n", main=main, xlab=xlab,ylab=ylab,...) # rh 2011-03-23 reverse ylim added
+axis(2, at=tickpos, labels=y.lab, cex.axis=0.7, las=2)
+if(is.null(col)){
+for(k in 1:length(confidences)) {
+ for(l in 1:length(factorlist)) {
+ lines(as.data.frame(confidences[[k]])[factorlist[l],],
+ c(l+k/distance, l+k/distance), t="b", col=length(cumsum(n2)[cumsum(n2) < k])+1, lty=lty[k])}
+ }
+} else {
+col <- rep(col, n2)
+for(k in 1:length(confidences)) {
+ for(l in 1:length(factorlist)) {
+ lines(as.data.frame(confidences[[k]])[factorlist[l],],
+ c(l+k/distance, l+k/distance), t="b", col=col[k], lty=lty[k])}
+ }
+}
+
+# doing nicer legend labels
+if(is.null(splitnames)==FALSE){
+ names(confidences) <- splitnames
+}
+
+if(leg == TRUE){
+ if(is.null(col)){
+ ##col <- rep(1:length(n2), each=n2) rh 2011-03-18
+ col <- rep(1:length(n2), n2)
+## legend(legpos, rev(paste(names(confidences))), col=rev(col), lty=rev(lty))
+ legend(legpos, paste(names(confidences)), col=col, lty=lty)
+ } else {
+## legend(legpos, rev(paste(names(confidences))), col=rev(col), lty=rev(lty))
+ legend(legpos, paste(names(confidences)), col=col, lty=lty)
+ }
+}
+
+invisible(list(confints=confidences1)) #rh 2011-03-18
+
+}
+
+
diff --git a/R/plotICC.Rm.R b/R/plotICC.Rm.R
index c1eab1d..501a095 100644
--- a/R/plotICC.Rm.R
+++ b/R/plotICC.Rm.R
@@ -10,6 +10,7 @@ function(object, item.subset = "all", empICC = NULL, empCI = NULL, mplot = NULL,
X <- object$X
if (is.null(col)) col <- 1:(max(apply(X,2,max,na.rm=TRUE))+1)
+ main.arg <- main # rh added 2010-11-23 otherwise always same item in title if NULL
# some sanity checks
@@ -84,7 +85,7 @@ if (is.null(empICC)) {
yp <- as.matrix(p.list[[i]])
yy <- yp[th.ord,]
- if(is.null(main)) main<-paste("ICC plot for item ",textlab[i]) # rh 2010-03-06
+ if(is.null(main.arg)) main<-paste("ICC plot for item ",textlab[i]) # rh 2010-03-06
matplot(sort(theta),yy,type="l",lty=lty,col=col,
#main=paste("ICC plot for item ",textlab[i]),xlim=xlim, # replaced to allow for user titles rh 2010-03-06
main=main, xlim=xlim,
@@ -105,7 +106,7 @@ if (is.null(empICC)) {
yp <- as.matrix(p.list[[i]])
yy <- yp[th.ord,]
- if(is.null(main)) main<-paste("ICC plot for item ",textlab[i]) # rh 2010-03-06
+ if(is.null(main.arg)) main<-paste("ICC plot for item ",textlab[i]) # rh 2010-03-06
matplot(sort(theta),yy,type="l",lty=lty,col=col,
#main=paste("ICC plot for item ",textlab[i]),xlim=xlim, # replaced to allow for user titles rh 2010-03-06
main=main, xlim=xlim,
diff --git a/R/plotPWmap.R b/R/plotPWmap.R
index 05a75b9..6b5eb08 100644
--- a/R/plotPWmap.R
+++ b/R/plotPWmap.R
@@ -2,8 +2,8 @@
function(object, pmap=FALSE, imap=TRUE, item.subset="all", person.subset="all",
mainitem="Item Map", mainperson="Person Map",
mainboth="Item/Person Map", latdim="Latent Dimension",
- tlab="Infit t statistic", pp=NULL, cex.gen=0.6,
- person.pch=22, item.pch=23, personCI=NULL, itemCI=NULL)
+ tlab="Infit t statistic", pp=NULL, cex.gen=0.6, cex.pch=1,
+ person.pch=1, item.pch=16, personCI=NULL, itemCI=NULL, horiz=FALSE)
{
def.par <- par(no.readonly = TRUE) ## save default, for resetting...
@@ -216,31 +216,60 @@ function(object, pmap=FALSE, imap=TRUE, item.subset="all", person.subset="all",
maintitle <- mainboth
}
+
par(mar=c(5,4,4,2))
- plot(xrange,yrange, xlim=xrange, ylim=yrange, main=maintitle,
- ylab=latdim, xlab=tlab, type="n")
- abline(v=c(-2,2),col="lightgreen")
+
+ if (!horiz){ # rh 2010-12-09
+ plot(xrange,yrange, xlim=xrange, ylim=yrange, main=maintitle,
+ ylab=latdim, xlab=tlab, type="n")
+ abline(v=c(-2,2),col="lightgreen")
+ } else {
+ plot(yrange,xrange, xlim=yrange, ylim=xrange, main=maintitle,
+ ylab=tlab, xlab=latdim, type="n")
+ abline(h=c(-2,2),col="lightgreen")
+ }
if (pmap) { ## person map
zt <- pfitZ
- if (pci>0) ## draw confidence intervals
- arrows(zt,ploc+pci*pse, zt,ploc-pci*pse, angle=90, code=3, length=0.04,
- col=personCI$col, lty=personCI$lty)
- points(zt,ploc,pch=person.pch,cex=0.6)
- text(zt,ploc,names(ploc),cex=cex.gen,pos=4)
+ if (!horiz){
+ if (pci>0) ## draw confidence intervals
+ arrows(zt,ploc+pci*pse, zt,ploc-pci*pse, angle=90, code=3, length=0.04,
+ col=personCI$col, lty=personCI$lty)
+ points(zt,ploc,pch=person.pch,cex=cex.pch)
+ text(zt,ploc,names(ploc),cex=cex.gen,pos=4)
+ } else {
+ if (pci>0) ## draw confidence intervals
+ arrows(ploc+pci*pse, zt,ploc-pci*pse, zt, angle=90, code=3, length=0.04,
+ col=personCI$col, lty=personCI$lty)
+ points(ploc, zt, pch=person.pch,cex=cex.pch)
+ text(ploc, zt, names(ploc),cex=cex.gen,pos=4)
+ }
}
+
+
+
if (imap) { ## item map
if (dRm)
zt <- ifitZ
else
zt <- rep(ifitZ,times=tl)
- if (ici>0) ## draw confidence intervals
- arrows(zt,iloc+ici*ise, zt,iloc-ici*ise, angle=90, code=3, length=0.04,
- col=itemCI$col, lty=itemCI$lty)
- points(zt,iloc,pch=item.pch,cex=0.6)
- text(zt,iloc,rownames(tt),cex=cex.gen,pos=4)
+ if (!horiz){
+ if (ici>0) ## draw confidence intervals
+ arrows(zt,iloc+ici*ise, zt,iloc-ici*ise, angle=90, code=3, length=0.04,
+ col=itemCI$col, lty=itemCI$lty)
+ points(zt,iloc,pch=item.pch,cex=cex.pch)
+ text(zt,iloc,rownames(tt),cex=cex.gen,pos=4)
+ } else {
+ if (ici>0) ## draw confidence intervals
+ arrows(iloc+ici*ise, zt,iloc-ici*ise,zt, angle=90, code=3, length=0.04,
+ col=itemCI$col, lty=itemCI$lty)
+ points(iloc, zt,pch=item.pch,cex=cex.pch)
+ text(iloc,zt, rownames(tt),cex=cex.gen,pos=4)
+ }
}
par(def.par)
+
+ invisible(NULL)
}
diff --git a/R/predict.ppar.R b/R/predict.ppar.R
old mode 100644
new mode 100755
diff --git a/R/print.gof.R b/R/print.gof.R
old mode 100644
new mode 100755
diff --git a/R/print.logLik.eRm.r b/R/print.logLik.eRm.R
similarity index 100%
rename from R/print.logLik.eRm.r
rename to R/print.logLik.eRm.R
diff --git a/R/rostdeviance.r b/R/rostdeviance.r
old mode 100644
new mode 100755
diff --git a/R/summary.MLoef.r b/R/summary.MLoef.r
index 52cd288..f2ceb92 100644
--- a/R/summary.MLoef.r
+++ b/R/summary.MLoef.r
@@ -1,37 +1,39 @@
-summary.MLoef <- function(object,...)
+summary.MLoef <- function(object, ...)
{
-#print method for object of class "MLoef" (MLoef)
+# summary method for object of class "MLoef" (MLoef)
-# prepare message for split criteria
+ # prepare message for split criteria
if( length(object$splitcr) == 1){
- if( (object$splitcr == "median") | (object$splitcr == "mean")){ spl <- object$splitcr }
+ if( (object$splitcr == "median") | (object$splitcr == "mean") ){
+ spl <- object$splitcr
+ }
+ } else {
+ spl <- "user-defined"
}
- else{ spl <- "user-defined" }
-#
+
# if(!is.null(object$warning)){
# if(object$splitcr == "median") cat("Warning: Item(s)",paste(names(object$warning),collapse=", "),"with raw score equal to the median assigned to the lower raw score group!\n")
# if(object$splitcr == "mean") cat("Warning: Item(s)",paste(names(object$warning),collapse=", "),"with raw score equal to the mean assigned to the lower raw score group!\n")
# }
+
cat("\n")
cat("Martin-Loef-Test (split criterion: ",spl,")\n",sep="")
- cat("\n")
- cat("Group 1:\nItems: ")
- cat(paste(object$items1),sep=", ")
- cat("\nLog-Likelihood:",round(object$L1,3),"\n")
- cat(paste("k_1:",object$k[1]),"\n")
- cat("\n")
- cat("Group 2:\nItems: ")
- cat(paste(object$items2),sep=", ")
- cat("\nLog-Likelihood:",round(object$L2,3),"\n")
- cat(paste("k_2:",object$k[2]),"\n")
+ for(i in 1:length(object$i.groups)){
+ cat("\n")
+ cat("Group ",i,":\nItems: ",sep="")
+ cat(paste(object$i.groups[[i]]),sep=", ")
+ cat("\nLog-Likelihood:",round(object$subModels[[i]]$loglik,3),"\n")
+ }
+
cat("\n")
cat("Overall Rasch-Model:\n")
- cat("Log-Likelihood:",round(object$L0,3),"\n")
+ cat("Log-Likelihood:",round(object$fullModel$loglik,3),"\n")
cat("\n")
cat(paste("LR-value:",round(object$LR,3),"\n"))
cat(paste("Chi-square df:",round(object$df,3),"\n"))
cat(paste("p-value:",round(object$p.value,3)),"\n")
cat("\n")
+
}
diff --git a/R/summary.gof.R b/R/summary.gof.R
old mode 100644
new mode 100755
diff --git a/R/zzz.R b/R/zzz.R
index f6f05e0..9efd0f8 100644
--- a/R/zzz.R
+++ b/R/zzz.R
@@ -23,16 +23,3 @@ setMethod("plot",signature(x="performance",y="missing"),
function(x,y,...) {
.plot.performance(x,...)
})
-
-# .First.lib <- function( libname, pkgname, where) {
-# if (!require(methods)) {
-# stop("Require Methods package")
-# }
-# if (!require(gplots)) {
-# stop("Require gplots package")
-# }
-#
-# where <- match(paste("package:",pkgname, sep=""), search())
-# }
-
-
diff --git a/inst/doc/Rplots.pdf b/inst/doc/Rplots.pdf
new file mode 100644
index 0000000..b554dde
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+++ b/inst/doc/Rplots.pdf
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diff --git a/inst/doc/eRm.R b/inst/doc/eRm.R
old mode 100755
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old mode 100755
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old mode 100755
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index 3d0d896..0388b5d
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old mode 100755
new mode 100644
similarity index 100%
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copy to inst/doc/eRmvig.R
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old mode 100755
new mode 100644
similarity index 100%
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copy to inst/doc/eRmvig.Rnw
diff --git a/inst/doc/eRmvig.bib b/inst/doc/eRmvig.bib
old mode 100755
new mode 100644
index a0bbf07..de9c02c
--- a/inst/doc/eRmvig.bib
+++ b/inst/doc/eRmvig.bib
@@ -4,7 +4,7 @@
TITLE = {Was ist aus dem Rasch-Modell geworden? [What Happened with the Rasch Model?]},
JOURNAL = {Psychologische Rundschau},
VOLUME = {50},
- PAGES = {140-156}
+ PAGES = {140--156}
}
@article{Scheib:72,
@@ -13,7 +13,7 @@
TITLE = {{Das Lernen und L\"osen komplexer Denkaufgaben. [The learning and solving of complex reasoning items.]}},
JOURNAL = {Zeitschrift f\"ur Experimentelle und Angewandte Psychologie},
VOLUME = {3},
- PAGES = {456-506}
+ PAGES = {456--506}
}
@article{And:78,
@@ -22,7 +22,7 @@
TITLE = {A rating formulation for ordered response categories},
JOURNAL = {Psychometrika},
VOLUME = {43},
- PAGES = {561-573}
+ PAGES = {561--573}
}
@article{FiPa:91,
@@ -31,7 +31,7 @@
TITLE = {An extension of the rating scale model with an application to the measurement of change},
JOURNAL = {Psychometrika},
VOLUME = {56},
- PAGES = {637-651}
+ PAGES = {637--651}
}
@article{Mast:82,
@@ -40,7 +40,7 @@
TITLE = {A Rasch model for partial credit scoring},
JOURNAL = {Psychometrika},
VOLUME = {47},
- PAGES = {149-174}
+ PAGES = {149--174}
}
@article{FiPo:94,
@@ -49,7 +49,7 @@
TITLE = {An extension of the partial credit model with an application to the measurement of change},
JOURNAL = {Psychometrika},
VOLUME = {59},
- PAGES = {177-192}
+ PAGES = {177--192}
}
@article{LeVe:86,
@@ -58,7 +58,7 @@
TITLE = {Maximum likelihood estimation in generalized Rasch models},
JOURNAL = {Journal of educational statistics},
VOLUME = {11},
- PAGES = {183-196}
+ PAGES = {183--196}
}
@article{Ra:77,
@@ -67,7 +67,7 @@
TITLE = {On specific objectivity: An attempt at formalising the request for generality and validity of scientific statements},
JOURNAL = {Danish Yearbook of Philosophy},
VOLUME = {14},
- PAGES = {58-94}
+ PAGES = {58--94}
}
@article{GlVe:89,
@@ -76,7 +76,7 @@
TITLE = {Extensions of the partial credit model},
JOURNAL = {Psychometrika},
VOLUME = {54},
- PAGES = {635-659}
+ PAGES = {635--659}
}
@article{Mi:85,
@@ -85,7 +85,7 @@
TITLE = {Estimation of latent group effects},
JOURNAL = {Journal of the American Statistical Association},
VOLUME = {80},
- PAGES = {993-997}
+ PAGES = {993--997}
}
@article{Li:94,
@@ -94,7 +94,7 @@
TITLE = {More on the computation of higher-order derivatives of the elementary symmetric functions in the Rasch model},
JOURNAL = {Applied Psychological Measurement},
VOLUME = {18},
- PAGES = {53-62}
+ PAGES = {53--62}
}
@@ -104,7 +104,7 @@
TITLE = {The numerical solution of a set of conditional estimation equations},
JOURNAL = {Journal of the Royal Statistical Society, Series B},
VOLUME = {34},
- PAGES = {42-54}
+ PAGES = {42--54}
}
@article{And:73,
@@ -113,7 +113,7 @@
TITLE = {A goodness of fit test for the Rasch model},
JOURNAL = {Psychometrika},
VOLUME = {38},
- PAGES = {123-140}
+ PAGES = {123--140}
}
@article{Fisch:73,
@@ -122,7 +122,7 @@
TITLE = {The linear logistic test model as an instrument in educational research},
JOURNAL = {Acta Psychologica},
VOLUME = {37},
- PAGES = {359-374}
+ PAGES = {359--374}
}
@article{Riz:06,
@@ -142,7 +142,7 @@
TITLE = {The attack of the psychometricians},
JOURNAL = {Psychometrika},
VOLUME = {71},
- PAGES = {425-440}
+ PAGES = {425--440}
}
@article{Kub:05,
@@ -151,7 +151,7 @@
TITLE = {Psychological test calibration using the Rasch model: Some critical suggestions on traditional approaches},
JOURNAL = {International Journal of Testing},
VOLUME = {5},
- PAGES = {377-394}
+ PAGES = {377--394}
}
@article{CAnd:07,
@@ -207,7 +207,7 @@
YEAR = {1961},
TITLE = {On General Laws and the Meaning of Measurement in Psychology.},
BOOKTITLE = {Proceedings of the IV. Berkeley Symposium on Mathematical Statistics and Probability, Vol. IV},
- PAGES = {321-333},
+ PAGES = {321--333},
EDITOR = {},
PUBLISHER = {University of California Press},
ADDRESS = {Berkeley}
@@ -218,7 +218,7 @@
YEAR = {1995},
TITLE = {Derivations of the Rasch Model},
BOOKTITLE = {Rasch Models: Foundations, Recent Developments, and Applications},
- PAGES = {15-38},
+ PAGES = {15--38},
EDITOR = {G.H. Fischer and I.W. Molenaar},
PUBLISHER = {Springer},
ADDRESS = {New York}
@@ -229,7 +229,7 @@
YEAR = {1995},
TITLE = {Linear Logistic Models for Change},
BOOKTITLE = {Rasch Models: Foundations, Recent Developments, and Applications},
- PAGES = {157-180},
+ PAGES = {157--180},
EDITOR = {G.H. Fischer and I.W. Molenaar},
PUBLISHER = {Springer},
ADDRESS = {New York}
@@ -240,7 +240,7 @@
YEAR = {2004},
TITLE = {Estimation Methods for \uppercase{R}asch Measures},
BOOKTITLE = {Introduction to \uppercase{R}asch Measurement},
- PAGES = {25-48},
+ PAGES = {25--48},
EDITOR = {E. V. {Smith Jr.} and R. M. Smith},
PUBLISHER = {JAM Press},
ADDRESS = {Maple Grove, MN}
@@ -251,7 +251,7 @@
YEAR = {1995},
TITLE = {Polytomous Rasch Models and their Estimation},
BOOKTITLE = {Rasch models: Foundations, recent developments, and applications},
- PAGES = {271-292},
+ PAGES = {271--292},
EDITOR = {G.H. Fischer and I.W. Molenaar},
PUBLISHER = {Springer},
ADDRESS = {New York}
@@ -262,7 +262,7 @@
YEAR = {1995},
TITLE = {Estimation of Item Parameters},
BOOKTITLE = {Rasch models: Foundations, recent developements, and applications},
- PAGES = {39-51},
+ PAGES = {39--51},
EDITOR = {G.H. Fischer and I.W. Molenaar},
PUBLISHER = {Springer},
ADDRESS = {New York}
@@ -274,7 +274,7 @@
TITLE = {Marginal maximum likelihood estimation of item parameters: as application of an \uppercase{EM} algorithm},
JOURNAL = {Psychometrika},
VOLUME = {46},
- PAGES = {443-459}
+ PAGES = {443--459}
}
@article{Haberman:77,
@@ -283,7 +283,7 @@
TITLE = {Maximum likelihood estimates in exponential response models},
JOURNAL = {The Annals of Statistics},
VOLUME = {5},
- PAGES = {815-841}
+ PAGES = {815--841}
}
@article{Wright+Panchapakesan:1969,
@@ -292,7 +292,7 @@
TITLE = {A procedure for sample-free item analysis},
JOURNAL = {Educational and Psychological measurement},
VOLUME = {29},
- PAGES = {23-48}
+ PAGES = {23--48}
}
@BOOK{Wright+Masters:1982,
@@ -318,7 +318,7 @@
YEAR = {1992},
TITLE = {Objectivity in Measurement: A Philosophical History of \uppercase{R}asch's Separability Theorem},
BOOKTITLE = {Objective Measurement: Theory into Practice, Volume 1},
- PAGES = {29-60},
+ PAGES = {29--60},
EDITOR = {M. Wilson},
PUBLISHER = {Ablex},
ADDRESS = {Norwood, NJ}
@@ -329,7 +329,7 @@
YEAR = {2000},
TITLE = {The Growing Family of \uppercase{R}asch Models},
BOOKTITLE = {Essays on item response theory},
- PAGES = {25-42},
+ PAGES = {25--42},
EDITOR = {A. Boomsma and M.A.J. van Duijn and T.A.B. Snijders},
PUBLISHER = {Springer},
ADDRESS = {New York}
@@ -358,7 +358,7 @@
YEAR = {1989},
TITLE = {Aktueller \uppercase{S}tand und kritische \uppercase{W}\"urdigung der \uppercase{P}robabilistischen \uppercase{T}esttheorie. [\uppercase{C}urrent status and critical appreciation of probabilistic test theory]},
BOOKTITLE = {Moderne \uppercase{T}esttheorie: Ein Abriss samt neuesten Beitr\"agen},
- PAGES = {19-83},
+ PAGES = {19--83},
EDITOR = {K.D. Kubinger},
PUBLISHER = {Beltz},
ADDRESS = {Weinheim}
@@ -370,7 +370,7 @@
YEAR = {1992},
TITLE = {A Rasch Model with a Multivariate Distribution of Ability},
BOOKTITLE = {Objective Measurement: Theory into Practice, Volume 1},
- PAGES = {236-258},
+ PAGES = {236--258},
EDITOR = {M. Wilson},
PUBLISHER = {Ablex},
ADDRESS = {Norwood, NJ}
@@ -381,7 +381,7 @@
YEAR = {1995},
TITLE = {Linear and Repeated Measures Models for the Person Parameter},
BOOKTITLE = {Rasch Models: Foundations, Recent Developments, and Applications},
- PAGES = {203-214},
+ PAGES = {203--214},
EDITOR = {G.H. Fischer and I.W. Molenaar},
PUBLISHER = {Springer},
ADDRESS = {New York}
@@ -393,7 +393,7 @@
TITLE = {On the existence and uniqueness of maximum-likelihood estimates in the \uppercase{R}asch model},
JOURNAL = {Psychometrika},
VOLUME = {46},
- PAGES = {59-77}
+ PAGES = {59--77}
}
@INCOLLECTION{Fischer:1988,
@@ -401,7 +401,7 @@
YEAR = {1988},
TITLE = {Spezifische \uppercase{O}bjektvit\"at: \uppercase{E}ine wissenschaftstheoretische \uppercase{G}rundlage des \uppercase{R}asch-\uppercase{M}odells. [\uppercase{S}pecific objectivity: \uppercase{A}n epistemological foundation of the \uppercase{R}asch model.]},
BOOKTITLE = {Moderne Testtheorie},
- PAGES = {87-111},
+ PAGES = {87--111},
EDITOR = {K.D. Kubinger},
PUBLISHER = {Beltz},
ADDRESS = {Weinheim}
@@ -412,7 +412,7 @@
YEAR = {1983},
TITLE = {A General Latent Structure Model for Contingency Table Data},
BOOKTITLE = {Principals of Modern Psychological Measurement},
- PAGES = {117-138},
+ PAGES = {117--138},
EDITOR = {H. Wainer and S. Messik},
PUBLISHER = {Erlbaum},
ADDRESS = {Hillsdale, NJ}
@@ -424,7 +424,7 @@
TITLE = {Asymptotic properties of conditional maximum likelihood estimators},
JOURNAL = {Journal of the Royal Statistical Society, Series B},
VOLUME = {32},
- PAGES = {283-301}
+ PAGES = {283--301}
}
@INCOLLECTION{Glas+Verhelst:1995b,
@@ -432,7 +432,7 @@
YEAR = {1995},
TITLE = {Tests of Fit for Polytomous \uppercase{R}asch Models},
BOOKTITLE = {Rasch Models: Foundations, Recent Developments, and Applications},
- PAGES = {325-352},
+ PAGES = {325--352},
EDITOR = {G.H. Fischer and I.W. Molenaar},
PUBLISHER = {Springer},
ADDRESS = {New York}
@@ -454,7 +454,7 @@
TITLE = {Some \uppercase{M}antel-\uppercase{H}aenszel tests of \uppercase{R}asch model assumptions},
JOURNAL = {British Journal of Mathematical and Statistical Psychology},
VOLUME = {54},
- PAGES = {21-37}
+ PAGES = {21--37}
}
@INCOLLECTION{Glas+Verhelst:1995a,
@@ -462,7 +462,7 @@
YEAR = {1995},
TITLE = {Testing the \uppercase{R}asch model},
BOOKTITLE = {Rasch Models: Foundations, Recent Developments, and Applications},
- PAGES = {69-96},
+ PAGES = {69--96},
EDITOR = {G.H. Fischer and I.W. Molenaar},
PUBLISHER = {Springer},
ADDRESS = {New York}
@@ -473,7 +473,7 @@
YEAR = {2004},
TITLE = {Fit Analysis in Latent Trait Measurement Models.},
BOOKTITLE = {Introduction to Rasch Measurement},
- PAGES = {73-92},
+ PAGES = {73--92},
EDITOR = {E. S. Smith and R. M. Smith},
PUBLISHER = {JAM Press},
ADDRESS = {Maple Grove, MN}
@@ -484,7 +484,7 @@
YEAR = {1977},
TITLE = {Linear Logistic Trait Models: Theory and Application},
BOOKTITLE = {Structural Models of Thinking and Learning},
- PAGES = {203-225},
+ PAGES = {203--225},
EDITOR = {H. Spada and W. F. Kempf},
PUBLISHER = {Huber},
ADDRESS = {Bern}
@@ -495,7 +495,7 @@
YEAR = {1995},
TITLE = {Polytomous Mixed Rasch Models},
BOOKTITLE = {Rasch Models: Foundations, Recent Developments, and Applications},
- PAGES = {371-382},
+ PAGES = {371--382},
EDITOR = {G.H. Fischer and I.W. Molenaar},
PUBLISHER = {Springer},
ADDRESS = {New York}
@@ -506,7 +506,7 @@
YEAR = {1995},
TITLE = {The one parameter logistic test model},
BOOKTITLE = {Rasch Models: Foundations, Recent Developments, and Applications},
- PAGES = {215-238},
+ PAGES = {215--238},
EDITOR = {G.H. Fischer and I.W. Molenaar},
PUBLISHER = {Springer},
ADDRESS = {New York}
@@ -517,7 +517,7 @@
YEAR = {1994},
TITLE = {On Item Parameter Estimation in Certain Latent Trait Models},
BOOKTITLE = {Contributions to Mathematical Psychology, Psychometrics, and Methodology},
- PAGES = {249-263},
+ PAGES = {249--263},
EDITOR = {G.H. Fischer and D. Laming},
PUBLISHER = {Springer},
ADDRESS = {New York}
@@ -529,7 +529,7 @@
TITLE = {Testing and obtaining fit of data to the \uppercase{R}asch model},
JOURNAL = {British Journal of Mathematical and Statistical Psychology},
VOLUME = {33},
- PAGES = {205-233}
+ PAGES = {205--233}
}
@Manual{R:06,
@@ -549,7 +549,7 @@
TITLE = {Extended \uppercase{R}asch Modeling: The e\uppercase{R}m package for the application of \uppercase{IRT} models in \uppercase{R}},
JOURNAL = {Journal of Statistical Software},
VOLUME = {20(9)},
- PAGES = {1-20}
+ PAGES = {1--20}
}
@article{Warm:1989,
@@ -558,7 +558,7 @@
TITLE = {Weighted likelihood estimation of ability in item response theory},
JOURNAL = {Psychometrika},
VOLUME = {54},
- PAGES = {427�450}
+ PAGES = {427--450}
}
@article{Ponocny:2001,
@@ -567,7 +567,7 @@
TITLE = {Nonparametric goodness-of-fit tests for the \uppercase{R}asch model.},
JOURNAL = {Psychometrika},
VOLUME = {66},
- PAGES = {437-460}
+ PAGES = {437--460}
}
@INCOLLECTION{Birnbaum:1968,
@@ -575,7 +575,7 @@
YEAR = {1968},
TITLE = {Some latent trait models and their use in inferring an examinee's ability},
BOOKTITLE = {Statistical theories of mental test scores},
- PAGES = {395-479},
+ PAGES = {395--479},
EDITOR = {F. M. Lord and M. R. Novick},
PUBLISHER = {Addison-Wesley},
ADDRESS = {Reading, MA}
@@ -587,7 +587,7 @@
TITLE = {The \uppercase{R}asch sampler},
JOURNAL = {Journal of Statistical Software},
VOLUME = {20(4)},
- PAGES = {1-14}
+ PAGES = {1--14}
}
@article{FiSch:70,
@@ -596,7 +596,7 @@
TITLE = {Algorithmen und \uppercase{P}rogramme f\"ur das probabilistische \uppercase{T}estmodell von \uppercase{R}asch. [\uppercase{A}lgorithms and programs for \uppercase{R}asch's probabilistic test model.]},
JOURNAL = {Psychologische Beitr\"age},
VOLUME = {12},
- PAGES = {23-51}
+ PAGES = {23--51}
}
@article{Suarez+Glas:2003,
@@ -605,7 +605,7 @@
TITLE = {Evaluation of global testing procedures for item fit to the \uppercase{R}asch model.},
JOURNAL = {British Journal of Mathematical and Statistical Society},
VOLUME = {56},
- PAGES = {127-143}
+ PAGES = {127--143}
}
@article{Adams+Wilson+Wang:1997,
@@ -614,7 +614,7 @@
TITLE = {The multidimensional random coefficients multinomial logit model},
JOURNAL = {Applied Psychological Measurement},
VOLUME = {21},
- PAGES = {1-23}
+ PAGES = {1--23}
}
@article{Jannarone:1986,
@@ -623,7 +623,7 @@
TITLE = {Conjunctive item response theory model kernels},
JOURNAL = {Psychometrika},
VOLUME = {51},
- PAGES = {357-373}
+ PAGES = {357--373}
}
@article{,
@@ -641,7 +641,7 @@
TITLE = {\uppercase{CML} based estimation of extended \uppercase{R}asch models with the e\uppercase{R}m package in \uppercase{R}},
JOURNAL = {Psychology Science},
VOLUME = {49},
- PAGES = {26-43}
+ PAGES = {26--43}
}
@INCOLLECTION{Hoijtink+Boomsma:1995,
@@ -649,7 +649,7 @@
YEAR = {1995},
TITLE = {On person parameter estimation in the dichotomous \uppercase{R}asch model},
BOOKTITLE = {Rasch Models: Foundations, Recent Developments, and Applications},
- PAGES = {53-68},
+ PAGES = {53--68},
EDITOR = {G.H. Fischer and I.W. Molenaar},
PUBLISHER = {Springer},
ADDRESS = {New York}
diff --git a/inst/doc/eRmvig.pdf b/inst/doc/eRmvig.pdf
new file mode 100644
index 0000000..d9d1b73
Binary files /dev/null and b/inst/doc/eRmvig.pdf differ
diff --git a/man/MLoef.Rd b/man/MLoef.Rd
index 0a5ad65..74196fb 100644
--- a/man/MLoef.Rd
+++ b/man/MLoef.Rd
@@ -2,7 +2,7 @@
\alias{MLoef}
\alias{print.MLoef}
\alias{summary.MLoef}
-\title{Computation of Martin-L�f's LR-Test}
+\title{Computation of Martin-Loef's LR-Test}
\description{This LR-Test is based on item subgroup splitting.}
\usage{
MLoef(robj, splitcr = "median")
@@ -13,11 +13,14 @@ MLoef(robj, splitcr = "median")
\code{"median"} and \code{"mean"} split items in two groups based on their
items' raw scores. \code{splitcr} can also be a vector of length k (where k
denotes the number of items) that takes two distinct values to define groups
- used for the Martin-L�f Test.}
+ used for the Martin-Loef Test.}
}
-\details{The function currently does not allow for missing values.
- %The function can handle missing values, as long as every subject has at
- %least 2 valid responses in each group of items.
+\details{
+ This function implements a generalization of the Martin-Loef test for polytomous
+ items as proposed by Christensen, Bjorner, Kreiner & Petersen (2002), but does
+ currently not allow for missing values.
+ % The function can handle missing values, as long as every subject has at
+ % least 2 valid responses in each group of items.
If the split criterion is \code{"median"} or \code{"mean"} and one or more items'
raw scores are equal the median resp. mean, \code{MLoef} will issue a warning
@@ -29,28 +32,25 @@ MLoef(robj, splitcr = "median")
}
\value{
\code{MLoef} returns an object of class \code{MLoef} containing:
- \item{X01}{binary data matrix of \code{robj}}
- \item{model}{model of \code{robj}}
\item{LR}{LR-value}
\item{df}{degrees of freedom of the test statistic}
\item{p.value}{p-value of the test}
- \item{L0}{log-likelihood of the Rasch model}
- \item{L1}{log-likelihood of group 1}
- \item{L2}{log-likelihood of group 2}
- \item{theta.table.RM}{vector of persons' raw scores of the Rasch model}
- \item{theta.table.MLoef}{tabulation of persons' raw scores in the two groups}
- \item{items1}{list of items in group 1}
- \item{items2}{list of items in group 2}
- \item{k}{number of items in groups 1 and 2}
+ \item{fullModel}{the overall Rasch model}
+ \item{subModels}{a list containing the submodels}
+ \item{Lf}{log-likelihood of the full model}
+ \item{Ls}{list of the sub models' log-likelihoods}
+ \item{i.groups}{a list of the item groups}
\item{splitcr}{submitted split criterion}
\item{split.vector}{binary allocation of items to groups}
\item{warning}{items equalling median or mean for the respective split criteria}
\item{call}{the matched call}
}
\references{
-Fischer, G. H., and Molenaar, I. (1995). Rasch Models -- Foundations, Recent Developements, and Applications. Springer.
+Christensen, K. B., Bjorner, J. B., Kreiner S. & Petersen J. H. (2002). Testing unidimensionality in polytomous Rasch models. \emph{Psychometrika, (67)}4, 563--574.
-Rost, J. (2004). Lehrbuch Testtheorie -- Testkonstruktion. Bern: Huber.
+Fischer, G. H., and Molenaar, I. (1995). \emph{Rasch Models -- Foundations, Recent Developements, and Applications.} Springer.
+
+Rost, J. (2004). \emph{Lehrbuch Testtheorie -- Testkonstruktion.} Bern: Huber.
}
\author{Marco Maier, Reinhold Hatzinger}
%\note{}
diff --git a/man/eRm-package.Rd b/man/eRm-package.Rd
index 9f0cb0d..77b18fc 100644
--- a/man/eRm-package.Rd
+++ b/man/eRm-package.Rd
@@ -20,8 +20,8 @@ http://r-forge.r-project.org/projects/erm/.
\tabular{ll}{
Package: \tab eRm\cr
Type: \tab Package\cr
-Version: \tab 0.13-0\cr
-Date: \tab 2010-06-12\cr
+Version: \tab 0.13-4\cr
+Date: \tab 2011-03-23\cr
License: \tab GPL\cr
}
The basic input units for the functions are the person-item matrix X and the design matrix W.
@@ -45,7 +45,8 @@ ordered according to the rows of the data matrix.
\code{eRm}. \code{PCM} and \code{RSM} produce objects belonging to the classes
\code{RM} and \code{eRm}, whereas results of \code{LLTM}, \code{LRSM}, and \code{LLTM} are object of class \code{eRm}.
-We acknowledge Julian Gilbey for writing the \code{plotPWmap} function.
+We acknowledge Julian Gilbey for writing the \code{plotPWmap} function and Kathrin Gruber
+for the function \code{plotDIF}.
The \code{eRm} package contains functions from the packages \code{sna}, \code{gtools} and \code{ROCR}.
Thanks to Carter T. Butts, Gregory R. Warnes, and Tobias Sing et al.
}
diff --git a/man/plotDIF.Rd b/man/plotDIF.Rd
new file mode 100644
index 0000000..140abf6
--- /dev/null
+++ b/man/plotDIF.Rd
@@ -0,0 +1,114 @@
+\name{plotDIF}
+\alias{plotDIF}
+\title{
+Confidence intervals plot of item parameter estimates.
+}
+\description{
+Performs an plot of item parameter conficence intervals based on \code{LRtest} subgroup splitting.
+}
+\usage{
+plotDIF(object, item.subset = NULL, gamma = 0.95, main = NULL,
+ xlim = NULL, xlab = " ", ylab=" ", col = NULL,
+ distance = 10, splitnames=NULL, leg = FALSE, legpos="bottomleft", ...)
+}
+
+\arguments{
+ \item{object}{
+An object of class \code{LR} (if more objects should be plotted, the argument has to be defined as a \code{list}).
+}
+ \item{item.subset}{
+Subset of items to be plotted. Either a numeric vector indicating the items or a character vector indicating the itemnames.
+If nothing is defined (default), all items are plotted.
+}
+ \item{gamma}{
+The level for the item parameter's confidence limits (default is gamma = 0.95).
+}
+ \item{main}{
+Main title for the plot.
+}
+ \item{xlim}{
+Numeric vector of length 2, giving the x coordinates ranges of the plot (the y coordinates depend on the number of
+depicted items).
+}
+ \item{xlab}{
+Label for the x axis.
+}
+ \item{ylab}{
+Label for the y axis.
+}
+ \item{col}{
+By default the color for the drawn confidence lines is determined automatically whereas every group (split criterion)
+is depicted in the same color.
+}
+ \item{distance}{
+Distance between the drawn confidence lines, default is division by factor 10 .
+}
+ \item{splitnames}{
+For labeling the splitobjects in the legend (returns a nicer output).
+}
+ \item{leg}{
+If \code{TRUE} a legend is provided by default.
+}
+ \item{legpos}{
+Position of the legend with possible values \code{"bottomright"}, \code{"bottom"}, \code{"bottomleft"}, \code{"left"},
+\code{"topleft"}, \code{"top"}, \code{"topright"}, \code{"right"} and \code{"center"}. The default value for the legend
+is \code{"bottomright"}.
+}
+ \item{...}{
+Further options to be passed to \code{plot}.
+}
+
+}
+
+\details{
+ If there are items that cannot be estimated for some reasons, certainly these ones are not plotted.
+ For plotting several objects of class \code{LR}, the subgroup splitting by \code{LRtest} has to
+ be carried out for the same data set (or at least item subsets of it).
+
+ Plotting a certain subset of items could be useful if the objects of class \code{LR} contain a huge number
+ of estimated items.
+
+ The default level for the conficence limits is gamma = 0.95. (If the conficence limits should be
+ corrected it is useful to use a correction, e.g., Bonferroni: 1 - (1 - gamma) / number of estimated items.)
+}
+\value{
+\code{plotCI} returns a list containing the confidence limits of each group in each \code{LRtest} object.
+}
+
+\author{
+Kathrin Gruber, Reinhold Hatzinger
+}
+
+\seealso{
+\code{\link{LRtest}}, \code{\link{confint.threshold}}, \code{\link{thresholds}}
+}
+\examples{
+
+splitvec <- sample(1:3, 100, replace = TRUE)
+data(raschdat1)
+res <- RM(raschdat1)
+
+# LR-test on dichotomous Rasch model with user-defined split
+lrres <- LRtest(res, splitcr = splitvec, se = TRUE)
+# LR-test with mean split, standard errors for beta's
+lrres2 <- LRtest(res, split = "mean", se = TRUE)
+RMplotCI <- list(lrres, lrres2)
+
+# Confidence intervals plot with default assumptions
+plotDIF(RMplotCI)
+
+# Confidence intervals plot with Bonferroni correction
+plotDIF(RMplotCI, gamma = 1 - (0.05/10))
+
+# Confidence intervals plot for an item subset
+plotDIF(RMplotCI, item.subset=1:6)
+
+# with user defined group color and legend
+plotDIF(RMplotCI, col=c("red","blue"), leg=TRUE)
+
+# with names for the splitobjects
+plotDIF(RMplotCI, col=c("red","blue"), leg=TRUE,
+splitnames=c(paste(rep("User",3),1:3,sep=" "), paste(rep("Mean",2),1:2, sep=" ")))
+}
+
+\keyword{models}
diff --git a/man/plotPWmap.Rd b/man/plotPWmap.Rd
index efc69de..6c13d1b 100644
--- a/man/plotPWmap.Rd
+++ b/man/plotPWmap.Rd
@@ -15,9 +15,9 @@ plotPWmap(object, pmap = FALSE, imap=TRUE,
mainboth="Item/Person Map",
latdim = "Latent Dimension",
tlab = "Infit t statistic",
- pp = NULL, cex.gen = 0.6,
- person.pch = 22, item.pch = 23,
- personCI = NULL, itemCI = NULL)
+ pp = NULL, cex.gen = 0.6, cex.pch=1,
+ person.pch = 1, item.pch = 16,
+ personCI = NULL, itemCI = NULL, horiz=FALSE)
}
\arguments{
\item{object}{Object of class \code{Rm} or \code{dRm}}
@@ -47,8 +47,10 @@ plotPWmap(object, pmap = FALSE, imap=TRUE,
text and symbols should be magnified relative to the
default. Here \code{cex.gen} applies to all text labels. The
default is 0.6.}
+ \item{cex.pch}{applies to all plotting symbols. The
+ default is 1.}
\item{person.pch, item.pch}{Specifies the symbol used for plotting
- person data and item data respectively; the defaults are 22 and 23
+ person data and item data respectively; the defaults are 1 and 16
respectively. See \code{\link{points}} for more information
about \code{pch} values.}
\item{personCI, itemCI}{Plotting confidence intervals for the the
@@ -66,11 +68,13 @@ plotPWmap(object, pmap = FALSE, imap=TRUE,
The same goes for \code{itemCI}, except that the default settings
are \code{itemCI=list(gamma=0.95,col="red",lty="dotted")}.}
+ \item{horiz}{if \code{TRUE}, the plot is horizontal, i.e., the latent
+ dimension is on the x-axis. The default is \code{FALSE}.}
}
\details{
- This code uses vertical error bars rather than circles or boxes to
+ This code uses vertical(horizontal) error bars rather than circles or boxes to
indicate standard errors. It also offers the possibility of plotting
- item or person data on it own; this can considerably simplify the
+ item or person data on its own; this can considerably simplify the
reading of the plots for large datasets.
}
%\value{}
--
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