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

1 Citation (Scopus)
57 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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