Nothing
difGenLogistic<-function (Data, group, focal.names, anchor = NULL, match = "score",
type = "both", criterion = "LRT", alpha = 0.05, purify = FALSE,
nrIter = 10, p.adjust.method=NULL,save.output = FALSE, output = c("out", "default"))
{
if (purify & match[1] != "score")
stop("purification not allowed when matching variable is not 'score'",
call. = FALSE)
internalGenLog <- function() {
if (length(focal.names) == 1)
RES <- difLogistic(Data, group, focal.name = focal.names,
member.type = "group", match = match, type = type,
alpha = alpha, p.adjust.method = p.adjust.method,
purify = purify, nrIter = nrIter,
save.output = save.output, output = output)
else {
if (length(group) == 1) {
if (is.numeric(group)) {
gr <- Data[, group]
DATA <- Data[, (1:ncol(Data)) != group]
colnames(DATA) <- colnames(Data)[(1:ncol(Data)) !=
group]
}
else {
gr <- Data[, colnames(Data) == group]
DATA <- Data[, colnames(Data) != group]
colnames(DATA) <- colnames(Data)[colnames(Data) !=
group]
}
}
else {
gr <- group
DATA <- Data
}
Group <- rep(0, nrow(DATA))
DF <- length(focal.names)
DDF<-ifelse(type=="both",2*DF,DF)
for (i in 1:DF) Group[gr == focal.names[i]] <- i
Q <- switch(type, both = qchisq(1 - alpha, 2 * DF),
udif = qchisq(1 - alpha, DF), nudif = qchisq(1 -
alpha, DF))
if (!is.null(anchor)) {
dif.anchor <- anchor
if (is.numeric(anchor))
ANCHOR <- anchor
else {
ANCHOR <- NULL
for (i in 1:length(anchor)) ANCHOR[i] <- (1:ncol(DATA))[colnames(DATA) ==
anchor[i]]
}
}
else {
ANCHOR <- 1:ncol(DATA)
dif.anchor <- NULL
}
if (!purify | match[1] != "score" | !is.null(anchor)) {
PROV <- genLogistik(DATA, Group, match = match,
type = type, criterion = criterion, anchor = ANCHOR)
STATS <- PROV$stat
PVAL<-1-pchisq(STATS,DDF)
deltaR2 <- PROV$deltaR2
covMat <- PROV$covMat
if (max(STATS) <= Q) {
DIFitems <- "No DIF item detected"
logitPar <- PROV$parM1
}
else {
DIFitems <- (1:ncol(DATA))[STATS > Q]
logitPar <- PROV$parM1
for (idif in 1:length(DIFitems)) logitPar[DIFitems[idif],
] <- PROV$parM0[DIFitems[idif], ]
}
RES <- list(genLogistik = STATS, p.value=PVAL,logitPar = logitPar,
parM0 = PROV$parM0, covMat = covMat, deltaR2 = deltaR2,
alpha = alpha, thr = Q, DIFitems = DIFitems,
match = PROV$match, type = type, p.adjust.method = p.adjust.method,
adjusted.p = NULL, purification = purify,
names = colnames(DATA), anchor.names = dif.anchor,
focal.names = focal.names, criterion = criterion,
save.output = save.output, output = output)
if (!is.null(anchor) & match[1] == "score") {
RES$genLogistik[ANCHOR] <- NA
RES$logitPar[ANCHOR, ] <- NA
RES$parM0[ANCHOR, ] <- NA
RES$covMat[, , ANCHOR] <- NA
RES$deltaR2[ANCHOR] <- NA
for (i in 1:length(RES$DIFitems)) {
if (sum(RES$DIFitems[i] == ANCHOR) == 1)
RES$DIFitems[i] <- NA
}
RES$DIFitems <- RES$DIFitems[!is.na(RES$DIFitems)]
}
}
else {
nrPur <- 0
difPur <- NULL
noLoop <- FALSE
prov1 <- genLogistik(DATA, Group, match = match,
type = type, criterion = criterion)
stats1 <- prov1$stat
deltaR2 <- prov1$deltaR2
covMat <- prov1$covMat
if (max(stats1) <= Q) {
DIFitems <- "No DIF item detected"
logitPar <- prov1$parM1
noLoop <- TRUE
}
else {
dif <- (1:ncol(DATA))[stats1 > Q]
difPur <- rep(0, length(stats1))
difPur[dif] <- 1
repeat {
if (nrPur >= nrIter)
break
else {
nrPur <- nrPur + 1
nodif <- NULL
if (is.null(dif) == TRUE)
nodif <- 1:ncol(DATA)
else {
for (i in 1:ncol(DATA)) {
if (sum(i == dif) == 0)
nodif <- c(nodif, i)
}
}
prov2 <- genLogistik(DATA, Group, anchor = nodif,
match = match, type = type, criterion = criterion)
stats2 <- prov2$stat
deltaR2 <- prov2$deltaR2
covMat <- prov2$covMat
if (max(stats2) <= Q)
dif2 <- NULL
else dif2 <- (1:ncol(DATA))[stats2 > Q]
difPur <- rbind(difPur, rep(0, ncol(DATA)))
difPur[nrPur + 1, dif2] <- 1
if (length(dif) != length(dif2))
dif <- dif2
else {
dif <- sort(dif)
dif2 <- sort(dif2)
if (sum(dif == dif2) == length(dif)) {
noLoop <- TRUE
break
}
else dif <- dif2
}
}
}
prov1 <- prov2
stats1 <- stats2
PVAL<-1-pchisq(stats1,DDF)
deltaR2 <- deltaR2
covMat <- covMat
DIFitems <- (1:ncol(DATA))[stats1 > Q]
logitPar <- prov1$parM1
for (idif in 1:length(DIFitems)) logitPar[DIFitems[idif],
] <- prov1$parM0[DIFitems[idif], ]
}
if (!is.null(difPur)) {
ro <- co <- NULL
for (ir in 1:nrow(difPur)) ro[ir] <- paste("Step",
ir - 1, sep = "")
for (ic in 1:ncol(difPur)) co[ic] <- paste("Item",
ic, sep = "")
rownames(difPur) <- ro
colnames(difPur) <- co
}
RES <- list(genLogistik = stats1, p.value=PVAL,logitPar = logitPar,
parM0 = prov1$parM0, covMat = covMat, deltaR2 = deltaR2,
alpha = alpha, thr = Q, DIFitems = DIFitems,
match = prov1$match, type = type, p.adjust.method = p.adjust.method,
adjusted.p = NULL, purification = purify,
nrPur = nrPur, difPur = difPur, convergence = noLoop,
names = colnames(DATA), anchor.names = NULL,
focal.names = focal.names, criterion = criterion,
save.output = save.output, output = output)
}
if (!is.null(p.adjust.method)) {
nGroups <- length(RES$focal.names)
df <- switch(RES$type, both = 2 * nGroups, udif = nGroups,
nudif = nGroups)
pval<-1-pchisq(RES$genLogistik,df)
RES$adjusted.p <- p.adjust(pval, method = p.adjust.method)
if (min(RES$adjusted.p, na.rm = TRUE) > alpha)
RES$DIFitems <- "No DIF item detected"
else RES$DIFitems <- which(RES$adjusted.p < alpha)
}
class(RES) <- "genLogistic"
}
return(RES)
}
resToReturn <- internalGenLog()
if (save.output) {
if (output[2] == "default")
wd <- paste(getwd(), "/", sep = "")
else wd <- output[2]
fileName <- paste(wd, output[1], ".txt", sep = "")
capture.output(resToReturn, file = fileName)
}
return(resToReturn)
}
# METHODS
plot.genLogistic <- function (x, plot = "lrStat", item = 1, itemFit="best",pch = 8, number = TRUE, col = "red",
colIC = rep("black",length(x$focal.names)+1),
ltyIC = 1:(length(x$focal.names)+1), title=NULL, save.plot=FALSE,save.options=c("plot","default","pdf"),ref.name=NULL,...)
{
internalGenLog<-function(){
res <- x
plotType <- switch(plot, lrStat=1, itemCurve=2)
if (is.null(plotType)) return("Error: misspecified 'type' argument")
else {
if (plotType==1){
if (!number) {
plot(res$genLogistik, xlab = "Item", ylab = "Generalized logistic regression statistic",
ylim = c(0, max(c(res$genLogistik, res$thr) + 1,na.rm=TRUE)), pch = pch,
main = ifelse(is.null(title),"Generalized logistic regression",title))
if (!is.character(res$DIFitems))
points(res$DIFitems, res$genLogistik[res$DIFitems],
pch = pch, col = col)
}
else {
plot(res$genLogistik, xlab = "Item", ylab = "Generalized logistic regression statistic",
ylim = c(0, max(c(res$genLogistik, res$thr) + 1,na.rm=TRUE)), col = "white",
main = ifelse(is.null(title),"Generalized logistic regression",title))
text(1:length(res$genLogistik), res$genLogistik, 1:length(res$genLogistik))
if (!is.character(res$DIFitems))
text(res$DIFitems, res$genLogistik[res$DIFitems], res$DIFitems,
col = col)
}
abline(h = res$thr)
}
else {
it <- ifelse(is.character(item) | is.factor(item),
(1:length(res$names))[res$names==item],item)
if (is.na(res$logitPar[it,1])) stop("Selected item is an anchor item!",call.=FALSE)
if (itemFit=="best") logitPar <- res$logitPar[it,]
else logitPar<-res$parM0[it,]
s <- seq(0,length(res$genLogistik),0.1)
expit <- function(t) exp(t)/(1+exp(t))
mainName <- ifelse(is.null(title),ifelse(is.character(res$names[it]),res$names[it],paste("Item ", it, sep="")),title)
plot(s, expit(logitPar[1]+logitPar[2]*s), col = colIC[1], type = "l",
lty = ltyIC[1], ylim = c(0,1), xlab = "Score", ylab = "Probability",
main=mainName)
if (itemFit=="null" | (itemFit=="best" & !is.character(res$DIFitems) & sum(res$DIFitems==it)==1)){
for (i in 1:length(res$focal.names))
lines(s, expit(logitPar[1]+logitPar[2]*s+logitPar[2+i]+logitPar[2+length(res$focal.names)+i]*s),
col = colIC[1+i], lty = ltyIC[1+i])
legnames <- ifelse(is.null(ref.name),"Reference",ref.name)
if (is.character(res$focal.names) | is.factor(res$focal.names)) legnames <- c(legnames,res$focal.names)
else{
for (t in 1:length(res$focal.names)) legnames <- c(legnames,paste("Focal ",
res$focal.names[t],sep=""))
}
legend(0, 1, legnames, col = colIC, lty = ltyIC, bty = "n")
}
}
}
}
internalGenLog()
if (save.plot){
plotype<-NULL
if (save.options[3]=="pdf") plotype<-1
if (save.options[3]=="jpeg") plotype<-2
if (is.null(plotype)) cat("Invalid plot type (should be either 'pdf' or 'jpeg').","\n","The plot was not captured!","\n")
else {
if (save.options[2]=="default") wd<-paste(getwd(),"/",sep="")
else wd<-save.options[2]
fileName<-paste(wd,save.options[1],switch(plotype,'1'=".pdf",'2'=".jpg"),sep="")
if (plotype==1){
{
pdf(file=fileName)
internalGenLog()
}
dev.off()
}
if (plotype==2){
{
jpeg(filename=fileName)
internalGenLog()
}
dev.off()
}
cat("The plot was captured and saved into","\n"," '",fileName,"'","\n","\n",sep="")
}
}
else cat("The plot was not captured!","\n",sep="")
}
print.genLogistic<-function (x, ...)
{
res <- x
cat("\n")
mess1 <- switch(res$type, both = " both types of ", nudif = " nonuniform ",
udif = " uniform ")
cat("Detection of", mess1, "Differential Item Functioning",
"\n", "using Generalized logistic regression method,",
"\n", sep = "")
if (res$purification & is.null(res$anchor.names) & res$match ==
"score")
pur <- "with "
else pur <- "without "
cat(pur, "item purification ", sep = "")
cat("and with ", length(res$focal.names), " focal groups",
"\n", "\n", sep = "")
if (is.character(res$focal.names) | is.factor(res$focal.names)) {
cat("Focal groups:", "\n")
nagr <- cbind(res$focal.names)
rownames(nagr) <- rep("", nrow(nagr))
colnames(nagr) <- ""
print(nagr, quote = FALSE)
cat("\n")
}
cat("DIF flagging criterion:", ifelse(res$criterion == "Wald",
"Wald test", "Likelihood ratio test"), "\n", "\n")
if (res$purification & is.null(res$anchor.names) & res$match ==
"score") {
if (res$nrPur <= 1)
word <- " iteration"
else word <- " iterations"
if (!res$convergence) {
cat("WARNING: no item purification convergence after ",
res$nrPur, word, "\n", sep = "")
loop <- NULL
for (i in 1:res$nrPur) loop[i] <- sum(res$difPur[1,
] == res$difPur[i + 1, ])
if (max(loop) != length(res$genLogistik))
cat("(Note: no loop detected in less than ",
res$nrPur, word, ")", "\n", sep = "")
else cat("(Note: loop of length ", min((1:res$nrPur)[loop ==
length(res$genLogistik)]), " in the item purification process)",
"\n", sep = "")
cat("WARNING: following results based on the last iteration of the purification",
"\n", "\n")
}
else cat("Convergence reached after ", res$nrPur, word,
"\n", "\n", sep = "")
}
if (res$match[1] == "score")
cat("Matching variable: test score", "\n", "\n")
else cat("Matching variable: specified matching variable",
"\n", "\n")
if (is.null(res$anchor.names) | res$match != "score") {
itk <- 1:length(res$genLogistik)
cat("No set of anchor items was provided", "\n", "\n")
}
else {
itk <- (1:length(res$genLogistik))[!is.na(res$genLogistik)]
cat("Anchor items (provided by the user):", "\n")
if (is.numeric(res$anchor.names))
mm <- res$names[res$anchor.names]
else mm <- res$anchor.names
mm <- cbind(mm)
rownames(mm) <- rep("", nrow(mm))
colnames(mm) <- ""
print(mm, quote = FALSE)
cat("\n", "\n")
}
if (is.null(res$p.adjust.method))
cat("No p-value adjustment for multiple comparisons",
"\n", "\n")
else {
pAdjMeth <- switch(res$p.adjust.method, bonferroni = "Bonferroni",
holm = "Holm", hochberg = "Hochberg", hommel = "Hommel",
BH = "Benjamini-Hochberg", BY = "Benjamini-Yekutieli")
cat("Multiple comparisons made with", pAdjMeth, "adjustement of p-values",
"\n", "\n")
}
cat("Generalized Logistic regression statistic:", "\n", "\n")
nGroups <- length(res$focal.names)
df <- switch(res$type, both = 2 * nGroups, udif = nGroups,
nudif = nGroups)
pval <- round(1 - pchisq(res$genLogistik, df), 4)
if (is.null(res$p.adjust.method)) symb <- symnum(pval, c(0, 0.001, 0.01, 0.05, 0.1, 1), symbols = c("***",
"**", "*", ".", ""))
else symb <- symnum(res$adjusted.p, c(0, 0.001, 0.01, 0.05, 0.1, 1), symbols = c("***",
"**", "*", ".", ""))
m1 <- cbind(round(res$genLogistik[itk], 4), pval[itk])
if (!is.null(res$p.adjust.method)) m1<-cbind(m1,round(res$adjusted.p[itk],4))
m1 <- noquote(cbind(format(m1, justify = "right"), symb[itk]))
if (!is.null(res$names))
rownames(m1) <- res$names[itk]
else {
rn <- NULL
for (i in 1:nrow(m1)) rn[i] <- paste("Item", i, sep = "")
rownames(m1) <- rn[itk]
}
con <- c("Stat.", "P-value")
if (!is.null(res$p.adjust.method))
con <- c(con, "Adj. P")
con <- c(con, "")
colnames(m1) <- con
print(m1)
cat("\n")
cat("Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 ",
"\n")
cat("\n", "Detection threshold: ", round(res$thr, 4), " (significance level: ",
res$alpha, ")", "\n", "\n", sep = "")
if (is.character(res$DIFitems))
cat("Items detected as DIF items:", res$DIFitems, "\n",
"\n")
else {
mess2 <- switch(res$type, both = " ", nudif = " nonuniform ",
udif = " uniform ")
cat("Items detected as", mess2, "DIF items:", "\n", sep = "")
if (!is.null(res$names))
m2 <- res$names
else {
rn <- NULL
for (i in 1:length(res$genLogistik)) rn[i] <- paste("Item",
i, sep = "")
m2 <- rn
}
m2 <- cbind(m2[res$DIFitems])
rownames(m2) <- rep("", nrow(m2))
colnames(m2) <- ""
print(m2, quote = FALSE)
cat("\n", "\n")
}
cat("Effect size (Nagelkerke's R^2):", "\n", "\n")
cat("Effect size code:", "\n")
cat(" 'A': negligible effect", "\n")
cat(" 'B': moderate effect", "\n")
cat(" 'C': large effect", "\n", "\n")
r2 <- round(res$deltaR2, 4)
symb1 <- symnum(r2, c(0, 0.13, 0.26, 1), symbols = c("A",
"B", "C"))
symb2 <- symnum(r2, c(0, 0.035, 0.07, 1), symbols = c("A",
"B", "C"))
matR2 <- noquote(cbind(format(r2[itk], justify = "right"),
symb1[itk], symb2[itk]))
if (!is.null(res$names))
rownames(matR2) <- res$names[itk]
else {
rn <- NULL
for (i in 1:nrow(matR2)) rn[i] <- paste("Item", i, sep = "")
rownames(matR2) <- rn[itk]
}
colnames(matR2) <- c("R^2", "ZT", "JG")
print(matR2)
cat("\n")
cat("Effect size codes:", "\n")
cat(" Zumbo & Thomas (ZT): 0 'A' 0.13 'B' 0.26 'C' 1", "\n")
cat(" Jodoin & Gierl (JG): 0 'A' 0.035 'B' 0.07 'C' 1", "\n")
if (!x$save.output)
cat("\n", "Output was not captured!", "\n")
else {
if (x$output[2] == "default")
wd <- paste(getwd(), "/", sep = "")
else wd <- x$output[2]
fileName <- paste(wd, x$output[1], ".txt", sep = "")
cat("\n", "Output was captured and saved into file",
"\n", " '", fileName, "'", "\n", "\n", sep = "")
}
}
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