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The Rank-2PL IRT Models for Forced-Choice Questionnaires: Maximum Marginal Likelihood Estimation with an EM Algorithm

Author

Listed:
  • Jianbin Fu

    (Educational Testing Service)

  • Xuan Tan

    (Educational Testing Service)

  • Patrick C. Kyllonen

    (Educational Testing Service)

Abstract

The rank two-parameter logistic (Rank-2PL) item response theory models refer to a set of models applying the 2PL model in a sequential ranking process that occurs in forced-choice questionnaires. The multi-unidimensional pairwise preference with 2PL model (MUPP-2PL) is a Rank-2PL model for items with two statements. Focusing on items with three statements, we develop a maximum marginal likelihood estimation with an expectation-maximization algorithm to estimate item parameters and their standard errors. A simulation study is conducted to check parameter recovery, and then the model is applied to a real dataset. Finally, the findings are summarized and discussed, and future research is suggested.

Suggested Citation

  • Jianbin Fu & Xuan Tan & Patrick C. Kyllonen, 2025. "The Rank-2PL IRT Models for Forced-Choice Questionnaires: Maximum Marginal Likelihood Estimation with an EM Algorithm," Journal of Educational and Behavioral Statistics, , vol. 50(3), pages 497-525, June.
    • Handle: RePEc:sae:jedbes:v:50:y:2025:i:3:p:497-525
    DOI: 10.3102/10769986241256030
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