Updated r script for analysis

RProject/pcm.R

@@ -24,7 +24,7 @@ pcm_analysis <- function(df=NULL,treatment='TT',irtmodel='PCM2',method='MML') {
   nbitems <- sum(sapply(1:20,function(x) paste0('item',x)) %in% colnames(df))
   resp <- df[,sapply(seq(1,nbitems),function(x) paste0('item',x))]
   if (method=='MML') {
-    tam1 <-  tam.mml.mfr(resp=resp,Y=df[,treatment],irtmodel = irtmodel,est.variance = T,verbose=F)
+    tam1 <-  tam.mml(resp=resp,Y=df[,treatment],irtmodel = irtmodel,est.variance = T,verbose=F)
   }
   if (method=='JML') {
     tam1 <- tam.jml(resp=resp,group=1+df[,treatment])

Scripts/Analysis/NoDIF/pcm_nodif_100.do

@@ -2,7 +2,7 @@
 * Date : 2024-01-23
 * Stata version : Stata 18 SE
 *
-    * This program analyses simulated data without DIF through a partial credit model
+* This program analyses simulated data accounting for DIF through a partial credit model
 *
 * ado-files needed : - pcm (version 5.5 October 25, 2023, available on gitea)
 *
@@ -51,4 +51,5 @@
   * log close
 
 
+
 pcm item1 item2 item3 item4, categorical(tt)