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Qi Huang; Daniel M. Bolt; Weicong Lyu – Large-scale Assessments in Education, 2024
Large scale international assessments depend on invariance of measurement across countries. An important consideration when observing cross-national differential item functioning (DIF) is whether the DIF actually reflects a source of bias, or might instead be a methodological artifact reflecting item response theory (IRT) model misspecification.…
Descriptors: Test Items, Item Response Theory, Test Bias, Test Validity
Chengyu Cui; Chun Wang; Gongjun Xu – Grantee Submission, 2024
Multidimensional item response theory (MIRT) models have generated increasing interest in the psychometrics literature. Efficient approaches for estimating MIRT models with dichotomous responses have been developed, but constructing an equally efficient and robust algorithm for polytomous models has received limited attention. To address this gap,…
Descriptors: Item Response Theory, Accuracy, Simulation, Psychometrics
Chen, Jianan; van Laar, Saskia; Braeken, Johan – Large-scale Assessments in Education, 2023
A general validity and survey quality concern with student questionnaires under low-stakes assessment conditions is that some responders will not genuinely engage with the questionnaire, often with more random response patterns as a result. Using a mixture IRT approach and a meta-analytic lens across 22 educational systems participating in TIMSS…
Descriptors: Elementary Secondary Education, International Assessment, Achievement Tests, Foreign Countries
Kim, Nana; Bolt, Daniel M. – Educational and Psychological Measurement, 2021
This paper presents a mixture item response tree (IRTree) model for extreme response style. Unlike traditional applications of single IRTree models, a mixture approach provides a way of representing the mixture of respondents following different underlying response processes (between individuals), as well as the uncertainty present at the…
Descriptors: Item Response Theory, Response Style (Tests), Models, Test Items