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Added theta estimation methods

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Corentin Choisy
2025-05-06 08:31:24 +02:00
parent a70686cae0
commit 28e43dee33
6 changed files with 34 additions and 8 deletions
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14
R/pcm.R
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@ -10,11 +10,15 @@
#' @param grp string containing the name of the column where an optional group membership variable is stored in df
#' @param dif.items vector containing the list of indexes in "items" corresponding to dif items
#' @param type.dif vector containing DIF form for each item specified in dif.items. 1 is homogeneous DIF, 0 is heterogeneous DIF
#' @param verbose set to TRUE to print a detailed output, FALSE otherwise
#' @param fit string determining the optimization algorithm. Values "ucminf" or "nlminb" ar recommended
#' @param method.theta string determining the estimation method for individual latent variable values. Either "eap", "mle" or "wle"
#' @return A data.frame containing various model outputs
#' @import vcrpart
#' @import PP
#' @export
pcm <- function(df=NULL,items=NULL,grp=NULL,dif.items=NULL,type.dif=NULL,verbose=T,fit="ucminf") {
pcm <- function(df=NULL,items=NULL,grp=NULL,dif.items=NULL,type.dif=NULL,verbose=T,fit="ucminf",method.theta="eap") {
##### Detecting errors
if (any(!(items %in% colnames(df)))) {
@ -205,7 +209,13 @@ pcm <- function(df=NULL,items=NULL,grp=NULL,dif.items=NULL,type.dif=NULL,verbose
}
}
theta <- -1*ranef(mod,norm=F)+ifelse(grp==1,beta,0)
if (method.theta=="eap") {
theta <- c(-1*ranef(mod,norm=F)+ifelse(grp==1,beta,0))
} else if (method.theta=="wle") {
theta <- PP::PP_gpcm(as.matrix(df[,items]),t(restab),rep(1,length(items)))$resPP$resPP[,1]
} else if (method.theta=="mle") {
theta <- PP::PP_gpcm(as.matrix(df[,items]),t(restab),rep(1,length(items)),type="mle")$resPP$resPP[,1]
}
resid <- apply(matrix(1:nbitems,ncol=length(nbitems)),1, function(k) sapply(1:nrow(df), function(j) res_ij(theta[j],restab[k,],df[j,items[k]],beta=0)))
colnames(resid) <- items_o