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序数测量不变性检验×项目反应理论 (IRT)×
领域心理测量学心理测量学
方法族Latent structureLatent structure
起源年份1984–20111952–1968
提出者Roger Millsap; Bengt MuthénFrederic M. Lord (and Allan Birnbaum for the 2PL/3PL models)
类型Multi-group model comparisonProbabilistic measurement model
开创性文献Millsap, R. E. (2011). Statistical Approaches to Measurement Invariance. Routledge. ISBN: 978-1848728936Lord, F. M. & Novick, M. R. (1968). Statistical Theories of Mental Test Scores. Addison-Wesley. link ↗
别名ordinal MI, measurement invariance for ordinal data, ordinal CFA invariance, categorical measurement invarianceIRT, latent trait theory, item characteristic curve theory, modern test theory
相关65
摘要Ordinal measurement invariance testing evaluates whether a multi-group confirmatory factor model holds equivalent measurement properties across groups when scale items are ordinal — such as Likert-type response scales. It uses polychoric correlations and categorical estimators (WLSMV/DWLS) rather than Pearson-based methods, correcting the systematic bias that arises when ordinal data are treated as continuous.Item response theory models the probability that a respondent answers an item correctly (or endorses it) as a function of the respondent's latent trait level and the item's own statistical properties — difficulty, discrimination, and guessing. Unlike classical test theory, IRT places persons and items on the same scale, yielding measurement that is sample-independent for items and test-independent for persons.
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  1. v1
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  3. PUBLISHED

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ScholarGate方法对比: Ordinal Measurement Invariance · Item Response Theory. 于 2026-06-20 检索自 https://scholargate.app/zh/compare