Complex Latent Variable Modeling in Educational Assessment

Jean-Paul Fox*, Maarten Marsman, Joris Mulder, Josine Verhagen

*Corresponding author for this work

    Research output: Contribution to journalArticleAcademicpeer-review

    2 Citations (Scopus)
    78 Downloads (Pure)


    Bayesian item response theory models have been widely used in different research fields. They support measuring constructs and modeling relationships between constructs, while accounting for complex test situations (e.g., complex sampling designs, missing data, heterogenous population). Advantages of this flexible modeling framework together with powerful simulation-based estimation techniques are discussed. Furthermore, it is shown how the Bayes factor can be used to test relevant hypotheses in assessment using the College Basic Academic Subjects Examination (CBASE) data.

    Original languageEnglish
    Pages (from-to)1499-1510
    Number of pages12
    JournalCommunications in statistics. Simulation and computation
    Issue number5
    Publication statusPublished - 27 May 2016


    • Bayes factor
    • Bayesian modeling
    • Latent variable models
    • MCMC


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