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Item response theory: a statistical framework for educational and psychological measurement

Chen, Yunxiao ORCID: 0000-0002-7215-2324, Li, Xiaoou, Liu, Jingchen and Ying, Zhiliang (2023) Item response theory: a statistical framework for educational and psychological measurement. Statistical Science. ISSN 0883-4237 (In Press)

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Abstract

Item response theory (IRT) has become one of the most popular statistical mod- els for psychometrics, a eld of study concerned with the theory and techniques of psychological measurement. The IRT models are latent factor models tailored to the analysis, interpretation, and prediction of individuals' behaviors in answering a set of measurement items that typically involve categorical response data. Many impor- tant questions of measurement are directly or indirectly answered through the use of IRT models, including scoring individuals' test performances, validating a test scale, linking two tests, among others. This paper provides a review of item response the- ory, including its statistical framework and psychometric applications. We establish connections between item response theory and related topics in statistics, including em- pirical Bayes, nonparametric methods, matrix completion, regularized estimation, and sequential analysis. Possible future directions of IRT are discussed from the perspective of statistical learning.

Item Type: Article
Official URL: https://imstat.org/journals-and-publications/stati...
Additional Information: © 2023 Institute of Mathematical Sciences
Divisions: Statistics
Subjects: H Social Sciences > HA Statistics
Date Deposited: 21 Nov 2023 09:45
Last Modified: 16 May 2024 04:18
URI: http://eprints.lse.ac.uk/id/eprint/120810

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