MCMC estimation and some fit analysis of multidimensional IRT models

Anton Beguin, Cornelis A.W. Glas

Research output: Contribution to journalArticleAcademic

182 Citations (Scopus)

Abstract

A Bayesian procedure to estimate the three-parameter normal ogive model and a generalization of the procedure to a model with multidimensional ability parameters are presented. The procedure is a generalization of a procedure by Albert (1992) for estimating the two-parameter normal ogive model. The procedure supports analyzing data from multiple populations and incomplete designs. It is shown that restrictions can be imposed on the factor matrix for testing specific hypotheses about the ability structure. The technique is illustrated using simulated and real data.
Original languageEnglish
Pages (from-to)471-488
Number of pages17
JournalPsychometrika
Volume66
Issue number4
DOIs
Publication statusPublished - 2001

Keywords

  • IR-60246
  • Bayes estimates - full-information factor analysis - Gibbs sampler - item response theory - Markov chain Monte Carlo - multidimensional item response theory - normal ogive model
  • METIS-203946

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