Bayesian adaptive testing with polytomous items

Hao Ren, Seung W. Choi, Wim J. van der Linden*

*Corresponding author for this work

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    Abstract

    An extremely efficient MCMC method for Bayesian adaptive testing with polytomous items is explained both conceptually and in mathematical detail. Results from extensive simulation studies with different item pools, polytomous response models, calibration sample sizes, and test lengths are presented. In addition, the case of adaptive testing from pools with a mixture of dichotomous and polytomous items is addressed.

    Original languageEnglish
    Pages (from-to)427-449
    Number of pages23
    JournalBehaviormetrika
    Volume47
    Issue number2
    Early online date21 May 2020
    DOIs
    Publication statusPublished - 1 Jul 2020

    Keywords

    • UT-Hybrid-D
    • Bayesian optimality
    • Item calibration
    • MCMC algorithm
    • Polytomous response models
    • Adaptive testing

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