Nothing
#' Performs DIF detection using logistic regression method. (internal function)
#'
#' @description Internal function substituting the `difLogistik()` function of
#' the `difR` package.
#'
#' @keywords internal
#' @noRd
.difLogistic_edited <- function(Data, group, focal.name, anchor = NULL, member.type = "group",
match = "score", type = "both", criterion = "LRT",
alpha = 0.05, all.cov = FALSE, purify = FALSE, nrIter = 10,
p.adjust.method = NULL, puriadjType = "simple",
save.output = FALSE, output = c("out", "default")) {
if (member.type != "group" & member.type != "cont") {
stop("'member.type' must be either 'group' or 'cont'",
call. = FALSE
)
}
if (purify & !(match[1] %in% c("score", "zscore"))) {
stop("purification not allowed when matching variable is not 'score' or 'zscore'.",
call. = FALSE
)
}
internalLog <- function() {
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
}
if (member.type == "group") {
Group <- as.numeric(gr == focal.name)
} else {
Group <- gr
}
if (length(match) == dim(DATA)[1]) {
df <- data.frame(DATA, Group, match, check.names = F)
} else {
df <- data.frame(DATA, Group, check.names = F)
}
if (any(is.na(DATA))) {
warning("'Data' contains missing values. Observations with missing values are discarded.",
call. = FALSE
)
}
if (any(is.na(Group))) {
warning("'group' contains missing values. Observations with missing values are discarded.",
call. = FALSE
)
}
df <- df[complete.cases(df), ]
Group <- df[, "Group"]
DATA <- as.data.frame(df[, !(colnames(df) %in% c("Group", "match"))])
colnames(DATA) <- colnames(df)[!(colnames(df) %in% c("Group", "match"))]
if (length(match) > 1) {
if (any(is.na(match))) {
warning("'match' contains missing values. Observations with missing values are discarded.",
call. = FALSE
)
}
match <- df[, "match"]
}
Q <- switch(type,
both = qchisq(1 - alpha, 2),
udif = qchisq(1 - alpha, 1),
nudif = qchisq(1 - alpha, 1)
)
if (!is.null(anchor)) {
dif.anchor <- anchor
if (is.numeric(anchor)) {
ANCHOR <- anchor
} else {
ANCHOR <- which(colnames(DATA) %in% anchor)
}
} else {
ANCHOR <- 1:ncol(DATA)
dif.anchor <- NULL
}
if (purify) {
if (is.null(p.adjust.method)) {
puri.adj.method <- "none"
adj.method <- "none"
} else {
if (puriadjType == "simple") {
puri.adj.method <- "none"
adj.method <- p.adjust.method
} else {
puri.adj.method <- p.adjust.method
adj.method <- p.adjust.method
}
}
} else {
adj.method <- ifelse(is.null(p.adjust.method), "none", p.adjust.method)
}
DDF <- ifelse(type == "both", 2, 1)
if (!purify | !match[1] %in% c("score", "zscore") | !is.null(anchor)) {
PROV <- .Logistik_edited(DATA, Group,
member.type = member.type,
match = match, type = type, criterion = criterion, # there goes "zscore" string
anchor = ANCHOR, all.cov = all.cov
)
STATS <- PROV$stat
PVAL <- 1 - pchisq(STATS, DDF)
P.ADJUST <- p.adjust(PVAL, method = adj.method)
deltaR2 <- PROV$deltaR2
logitPar <- PROV$parM1
logitSe <- PROV$seM1
if (min(P.ADJUST, na.rm = T) >= alpha) {
DIFitems <- "No DIF item detected"
} else {
DIFitems <- which(P.ADJUST < alpha)
logitPar[DIFitems, ] <- PROV$parM0[DIFitems, ]
logitSe[DIFitems, ] <- PROV$seM0[DIFitems, ]
}
if (is.null(p.adjust.method)) {
adjusted.p <- NULL
} else {
adjusted.p <- P.ADJUST
}
RES <- list(
Logistik = STATS, p.value = PVAL, logitPar = logitPar,
logitSe = logitSe, parM0 = PROV$parM0, seM0 = PROV$seM0,
cov.M0 = PROV$cov.M0, cov.M1 = PROV$cov.M1, deltaR2 = deltaR2,
alpha = alpha, thr = Q, DIFitems = DIFitems,
member.type = member.type, match = PROV$match, # from PROV, string
type = type, p.adjust.method = p.adjust.method,
adjusted.p = adjusted.p,
purification = purify, names = colnames(DATA),
anchor.names = dif.anchor, criterion = criterion,
save.output = save.output, output = output,
Data = DATA, group = Group
)
if (!is.null(anchor) & match[1] == "score") { # match is "score"
RES$Logistik[ANCHOR] <- NA
RES$logitPar[ANCHOR, ] <- NA
RES$parM0[ANCHOR, ] <- NA
RES$deltaR2[ANCHOR] <- NA
RES$DIFitems <- RES$DIFitems[!RES$DIFitems %in% ANCHOR]
}
} else { # match is zscore or specified
nrPur <- 0
difPur <- NULL
noLoop <- FALSE
prov1 <- .Logistik_edited(DATA, Group, # the same as PROV
member.type = member.type,
match = match, type = type, criterion = criterion, # match as string "score"
all.cov = all.cov
)
stats1 <- prov1$stat
pval1 <- 1 - pchisq(stats1, DDF)
p.adjust1 <- p.adjust(pval1, method = puri.adj.method)
deltaR2 <- prov1$deltaR2
if (min(p.adjust1, na.rm = T) >= alpha) {
DIFitems <- "No DIF item detected"
logitPar <- prov1$parM1
logitSe <- prov1$seM1
noLoop <- TRUE
} else {
dif <- which(p.adjust1 < alpha)
difPur <- rep(0, length(stats1))
difPur[dif] <- 1 # mark DIF items as 1
repeat {
if (nrPur >= nrIter) {
break
} else {
nrPur <- nrPur + 1
if (is.null(dif)) {
nodif <- 1:ncol(DATA)
} else {
nodif <- which(!1:ncol(DATA) %in% dif)
}
prov2 <- .Logistik_edited(DATA, Group,
anchor = nodif,
member.type = member.type, match = match, # pur iter match - wants vector?
type = type, criterion = criterion, all.cov = all.cov
)
stats2 <- prov2$stat
pval2 <- 1 - pchisq(stats2, DDF)
p.adjust2 <- p.adjust(pval2, method = puri.adj.method)
deltaR2 <- prov2$deltaR2
if (min(p.adjust2, na.rm = T) >= alpha) {
dif2 <- NULL
} else {
dif2 <- which(p.adjust2 < alpha)
}
difPur <- rbind(difPur, rep(0, ncol(DATA)))
difPur[nrPur + 1, dif2] <- 1
dif <- sort(dif)
dif2 <- sort(dif2)
if (length(dif) != length(dif2)) {
dif <- dif2
} else {
if (all(dif == dif2)) {
noLoop <- TRUE
break
} else {
dif <- dif2
}
}
}
}
prov1 <- prov2
stats1 <- stats2
pval1 <- 1 - pchisq(stats1, DDF)
p.adjust1 <- p.adjust(pval1, method = adj.method)
deltaR2 <- deltaR2
logitPar <- prov1$parM1
logitSe <- prov1$seM1
if (min(p.adjust1, na.rm = T) >= alpha) {
DIFitems <- "No DIF item detected"
} else {
DIFitems <- which(!is.na(stats1) & p.adjust1 < alpha)
logitPar[DIFitems, ] <- prov1$parM0[DIFitems, ]
logitSe[DIFitems, ] <- prov1$seM0[DIFitems, ]
}
}
if (!is.null(difPur)) {
rownames(difPur) <- paste0("Step", 1:nrow(difPur) - 1)
colnames(difPur) <- colnames(DATA)
}
if (is.null(p.adjust.method)) {
adjusted.p <- NULL
} else {
adjusted.p <- p.adjust1
}
RES <- list(
Logistik = stats1, p.value = pval1, logitPar = logitPar,
logitSe = logitSe, parM0 = prov1$parM0, seM0 = prov1$seM0,
cov.M0 = prov1$cov.M0, cov.M1 = prov1$cov.M1,
deltaR2 = deltaR2, alpha = alpha, thr = Q, DIFitems = DIFitems,
member.type = member.type, match = prov1$match,
type = type, p.adjust.method = p.adjust.method,
adjusted.p = adjusted.p,
puriadjType = puriadjType,
purification = purify, nrPur = nrPur,
difPur = difPur, convergence = noLoop, names = colnames(DATA),
anchor.names = NULL, criterion = criterion, save.output = save.output,
output = output,
Data = DATA, group = Group
)
}
class(RES) <- "Logistic"
return(RES)
}
resToReturn <- internalLog()
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)
}
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.