Nothing
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# lzp
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########################################################################################
lzpoly <- function(matrix, Ncat,
NA.method="Pairwise", Save.MatImp=FALSE,
IP=NULL, IRT.PModel="GRM", Ability=NULL, Ability.PModel="EAP")
{
#
matrix <- as.matrix(matrix)
N <- dim(matrix)[1]; I <- dim(matrix)[2]; M <- Ncat-1
IP.NA <- is.null(IP); Ability.NA <- is.null(Ability)
# Sanity check - Data matrix adequacy:
Sanity.dma.poly(matrix, N, I, M)
# Estimate item parameters if not provided (polytomous):
IP.res <- estIP.poly(matrix, Ncat, IP, IRT.PModel)
IP <- IP.res[[1]]
IP.ltm <- IP.res[[2]]
# Estimate ability parameters if not provided (using 'ltm'):
Ability <- estAb.poly(matrix, IP.ltm, Ability, Ability.PModel)
# Dealing with missing values:
res.NA <- MissingValues.poly(matrix, Ncat, NA.method, Save.MatImp, IP, IRT.PModel, Ability, Ability.PModel)
matrix <- res.NA[[1]]
# Perfect response vectors allowed.
# Compute PFS:
P.CRF <- estP.CRF(I, Ncat, IRT.PModel, IP, Ability)
#
idty <- diag(Ncat)
f.scores <- function (x) {idty[x+1, ]}
matrix.01 <- matrix(unlist(lapply(t(matrix), f.scores)), byrow = TRUE, nrow = N)
# If there are answer options not chosen by any respondent then some entries in 'P.CRF' might be 0.
# Below all corresponding logs are set from Inf to 0.
# (Reason: They carry no information regarding aberrant response behavior).
log.P.CRF <- log(P.CRF)
log.P.CRF[is.infinite(log.P.CRF)] <- 0
#
l0p <- rowSums(matrix.01 * log.P.CRF, na.rm = TRUE)
El0p <- rowSums(P.CRF * log.P.CRF)
# Variance (two equivalent options up to time efficiency):
if (I*Ncat < 300)
{
ones.block <- vector("list", I)
ones.block[1:I] <- list(matrix(rep(1, Ncat^2), nrow = Ncat))
to.sum <- as.matrix(do.call(bdiag, ones.block))
V.row <- function(vect) {
log.vect <- log.P.CRF[vect[1],]
vect2 <- vect[2:(dim(P.CRF)[2]+1)]
tmp.part1 <- (vect2 %*% t(vect2)) * to.sum
tmp.part2 <- matrix(rep(log.vect, dim(P.CRF)[2]), nrow=dim(P.CRF)[2]) * to.sum
#
sum(tmp.part1 * tmp.part2 * (tmp.part2 - t(tmp.part2)))
}
Vl0p <- apply(cbind(1:N, P.CRF), 1, V.row)
} else
{
V.row <- function(vect) {
tot <- 0;
for (i in 1:I) {
log.vect <- log.P.CRF[vect[1], ((i-1)*Ncat+1):(Ncat*i)]
vect2 <- vect[((i-1)*Ncat+1):(Ncat*i)+1]
tmp.part1 <- vect2 %*% t(vect2)
tmp.part2 <- matrix(rep(log.vect, Ncat), nrow=Ncat)
#
tot <- tot + sum(tmp.part1 * tmp.part2 * (tmp.part2 - t(tmp.part2)));
}
tot
}
Vl0p <- apply(cbind(1:N,P.CRF),1,V.row)
}
res <- (l0p - El0p) / sqrt(Vl0p)
res[rowSums(is.na(matrix)) == I] <- NA
# Export results:
export.res.P(matrix, N, res, "lzpoly", vector("list", 5) , Ncat=Ncat, NA.method,
IRT.PModel, res.NA[[2]], Ability.PModel, res.NA[[3]], IP.NA, Ability.NA, res.NA[[4]])
}
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