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## File Name: linking_proc_itempars.R
## File Version: 0.09
linking_proc_itempars <- function(itempars)
{
#*** convert itempars to data frame
itempars <- as.data.frame( itempars )
weights_exist <- TRUE
# include wgt if there does not exist a fifth columm
if ( ncol(itempars)==4){
itempars$wgt <- 1
weights_exist <- FALSE
}
# extract studies
studies <- sort( paste( unique( itempars[,1] ) ) )
NS <- length(studies)
# extract items
items <- sort( paste( unique( itempars[,2] ) ) )
NI <- length(items)
# define a and b matrices
wgtM <- bM <- aM <- matrix(NA, nrow=NI, ncol=NS)
rownames(wgtM) <- rownames(bM) <- rownames(aM) <- items
colnames(wgtM) <- colnames(bM) <- colnames(aM) <- studies
# define item parameters
for (ss in studies){
itempars.ss <- itempars[ itempars[,1]==ss, ]
items_ss <- paste(itempars.ss[,2])
aM[ items_ss, ss ] <- itempars.ss[,3]
bM[ items_ss, ss ] <- itempars.ss[,4]
wgtM[ items_ss, ss ] <- itempars.ss[,5]
}
wgtM <- wgtM / matrix( rowSums( wgtM, na.rm=TRUE ), nrow=NI, ncol=NS )
est_pars <- ! is.na(wgtM)
is_1pl <- ( stats::sd(aM, na.rm=TRUE) < 1e-5 )
#--- output
res <- list(itempars=itempars, NS=NS, NI=NI, items=items, studies=studies,
wgtM=wgtM, aM=aM, bM=bM, est_pars=est_pars,
weights_exist=weights_exist, is_1pl=is_1pl)
return(res)
}
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