Statistical Foundations for Computerized Adaptive Testing with Response Revision

Research output: Contribution to journalArticlepeer-review

Abstract

The compatibility of computerized adaptive testing (CAT) with response revision has been a topic of debate in psychometrics for many years. The problem is to provide test takers opportunities to change their answers during the test, while discouraging deceptive strategies from their side and preserving the statistical efficiency of the traditional CAT. The estimating approach proposed in Wang et al. (Stat Sin 27(4):1987–2010, 2017), based on the nominal response model, allows test takers to provide more than one answer to each item during the test, which they all contribute to the interim and final ability estimation. This approach is here reformulated, extended to incorporate a larger class of polytomous and dichotomous item response theory models, and investigated with simulation studies under different test-taking strategies.

Original languageEnglish (US)
Pages (from-to)375-394
Number of pages20
JournalPsychometrika
Volume84
Issue number2
DOIs
StatePublished - Jun 15 2019

Keywords

  • computerized adaptive testing
  • dichotomous IRT models
  • item response theory (IRT)
  • large sample property
  • polytomous IRT models
  • response revision

ASJC Scopus subject areas

  • Psychology(all)
  • Applied Mathematics

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