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Box 1 library(R2jags) library(coda) library(lattice) library(R2WinBUGS) library(rjags) Posterior means are used as point estimates of the parameters of interest, for [M.sub.1] : [??] = 0.06 and [[??].sup.2] = 4.31 and for [mathematical expression not reproducible], and [[??].sup.2] = 0.52.
This imposes some restrictions on the design of the simulation because the number of prior distributions implemented in mirt was more limited than in rjags. As in the first study, we fitted the models twice using different priors:
Models were fitted in R ( through the prevalence and rjags packages interfacing with JAGS version 3.4.0 ( by using 2 chains containing 1,000 burn-in samples and 5,000 retained samples.
In fact, JAGS was chosen for the present work because it is easily interfaced with the R soft-ware through the use of the rjags library (Plummer, 2011).
Bayesian model fitting and model diagnostics such as the convergence of MCMC chains (Gelman and Hill 2007) were performed using the libraries rjags, coda and Runuran (Plummer et al.
All models were analyzed by calling JAGS 3.3.0 (Plummer 2012) from R 3.0.1 (R Core Team 2013) using the package rjags (Plummer 2013).