modelavgIRT <- function(personscores,personSEs,selectionindex,rescale=TRUE) {
##rescale personscores to have mean 0 and var 1
#rescale personSEs proportionally
if(rescale==TRUE){
for(i in seq(ncol(personscores))){
personscores[,i] <- (personscores[,i] - mean(personscores[,i]))/sd(personscores[,i])
personSEs[,i] <- personSEs[,i]/sd(personscores[,i])
}
}
##compute weights
weights <- c(rep(NA,length(selectionindex)))
for(i in seq(length(selectionindex))){
weights[i] <- sum(exp(-
.5*selectionindex[1:length(selectionindex)]+.5*selectionindex[i]))^(-1)
}
##compute averaged person scores
avg.personscore <- matrix(NA,nrow(personscores),1)
for(i in seq(nrow(personscores))){
avg.personscore[i,] <- sum(weights*personscores[i,])
}
##compute averaged person SEs
avg.personSE <- matrix(NA,nrow(personSEs),1)
for(i in seq(nrow(personSEs))){
avg.personSE[i,] <- sum(weights*sqrt(personSEs[i,]^2+(personscores[i,]-
avg.personscore[i,])^2))
}
output <- list(weights,avg.personscore,avg.personSE)
names(output) <- c(“weights”,”Average person score”,”Average person SE”)
return(output)
}