, Volume 66, Issue 4, pp 541–561

MCMC estimation and some model-fit analysis of multidimensional IRT models

  • A. A. Béguin
  • C. A. W. Glas

DOI: 10.1007/BF02296195

Cite this article as:
Béguin, A.A. & Glas, C.A.W. Psychometrika (2001) 66: 541. doi:10.1007/BF02296195


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.

Key words

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

Copyright information

© The Psychometric Society 2001

Authors and Affiliations

  • A. A. Béguin
    • 1
  • C. A. W. Glas
    • 1
  1. 1.University of TwenteThe Netherlands
  2. 2.CITO groupArnhemThe Netherlands

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