Bayesian adaptive testing with polytomous items

Hao Ren; Seung W. Choi; Wim J. van der Linden

doi:10.1007/s41237-020-00114-8

Bayesian adaptive testing with polytomous items

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

^*Corresponding author for this work

Research Methodology, Measurement and Data Analysis

Research output: Contribution to journal › Article › Academic › peer-review

2 Citations (Scopus)

20 Downloads (Pure)

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 language	English
Pages (from-to)	427-449
Number of pages	23
Journal	Behaviormetrika
Volume	47
Issue number	2
DOIs	https://doi.org/10.1007/s41237-020-00114-8
Publication status	E-pub ahead of print/First online - 21 May 2020

Keywords

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

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10.1007/s41237-020-00114-8Licence: CC BY

Ren-2020-Bayesian-adaptive-testing-with-polyFinal published version, 2.45 MBLicence: CC BY

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