Assessment of Bayesian Item Response Models

  • Jean-Paul Fox
Part of the Statistics for Social and Behavioral Sciences book series (SSBS)


The underlying assumptions of Bayesian item response models have to be examined to ensure their credibility and that meaningful inferences can be made. A set of tools will be discussed for testing model assumptions and hypotheses. This set of tools includes methods based on Bayesian residuals and predictive diagnostic checks. It will be shown that related computations can be done during an MCMC estimation procedure or afterwards using MCMC output.


Outlying Probability Local Independence Item Response Model Grade Response Model Posterior Predictive Distribution 
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Copyright information

© Springer New York 2010

Authors and Affiliations

  • Jean-Paul Fox
    • 1
  1. 1.Department of Research Methodology, Measurement, and Data Analysis Faculty of Behavioral SciencesUniversity of TwenteEnschedeThe Netherlands

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