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## File Name: IRT.marginal_posterior.R
## File Version: 0.13
IRT.marginal_posterior <- function(object, dim, remove_zeroprobs=TRUE, ...)
{
UseMethod("IRT.marginal_posterior")
}
IRT_marginal_posterior_compute <- function(object, dim,
remove_zeroprobs=TRUE, ... )
{
post <- IRT.posterior(object=object)
theta <- attr(post, "theta")
skill_names <- colnames(theta)
if ( ! is.numeric(dim) ){
dim <- match(dim, skill_names)
}
ND <- length(dim)
if (remove_zeroprobs){
ind <- which( colSums(post) > 0 )
post <- post[, ind, drop=FALSE]
theta <- theta[ ind,, drop=FALSE]
}
N <- nrow(post)
LD <- length(dim)
sp <- ""
for (ll in 1:LD){
sp <- paste0(sp,theta[,ll])
}
spu <- sort(unique(sp))
NS <- length(spu)
index_sp <- match(sp, spu)
marg_post <- matrix(NA, nrow=N, ncol=NS)
colnames(marg_post) <- spu
for (ss in 1:NS){
marg_post[,ss] <- rowSums( post[, index_sp==ss] )
}
# MAP estimate
map <- spu[ max.col(marg_post) ]
# skill design
theta <- strsplit(spu, split="")
theta <- matrix( as.numeric(unlist(theta)), ncol=ND, byrow=TRUE)
colnames(theta) <- skill_names[dim]
rownames(theta) <- spu
#-- output
res <- list(marg_post=marg_post, map=map, theta=theta)
return(res)
}
IRT.marginal_posterior.gdina <- IRT_marginal_posterior_compute
IRT.marginal_posterior.din <- IRT_marginal_posterior_compute
IRT.marginal_posterior.mcdina <- IRT_marginal_posterior_compute
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