Learn R Programming

mirt (version 1.17.1)

randef: Compute posterior estimates of random effect

Description

Stochastically compute random effects for MixedClass objects with Metropolis-Hastings samplers and averaging over the draws. Returns a list of the estimated effects.

Usage

randef(x, ndraws = 1000, thin = 10, return.draws = FALSE)

Arguments

x
an estimated model object from the mixedmirt function
ndraws
total number of draws to perform. Default is 1000
thin
amount of thinning to apply. Default is to use every 10th draw
return.draws
logical; return a list containing the thinned draws of the posterior?

Examples

Run this code
#make an arbitrary groups
covdat <- data.frame(group = rep(paste0('group', 1:49), each=nrow(Science)/49))

#partial credit model
mod <- mixedmirt(Science, covdat, model=1, random = ~ 1|group)
summary(mod)

effects <- randef(mod, ndraws = 2000, thin = 20)
head(effects$Theta)
head(effects$group)

Run the code above in your browser using DataLab