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

Jianbin Fu, Xuan Tan and Patrick C. Kyllonen
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Jianbin Fu: Educational Testing Service
Xuan Tan: Educational Testing Service
Patrick C. Kyllonen: Educational Testing Service

Journal of Educational and Behavioral Statistics, 2025, vol. 50, issue 3, 497-525

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.

Keywords: forced-choice questionnaire; rank two-parameter logistic model; item response theory; maximum marginal likelihood estimation; expectation-maximization algorithm (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:sae:jedbes:v:50:y:2025:i:3:p:497-525

DOI: 10.3102/10769986241256030

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