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순서형 측정 불변성 검증×문항 반응 이론 (IRT)×
분야심리측정학심리측정학
계열Latent structureLatent structure
기원 연도1984–20111952–1968
창시자Roger Millsap; Bengt MuthénFrederic M. Lord (and Allan Birnbaum for the 2PL/3PL models)
유형Multi-group model comparisonProbabilistic measurement model
원전Millsap, 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 ↗
별칭ordinal MI, measurement invariance for ordinal data, ordinal CFA invariance, categorical measurement invarianceIRT, latent trait theory, item characteristic curve theory, modern test theory
관련65
요약Ordinal 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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ScholarGate방법 비교: Ordinal Measurement Invariance · Item Response Theory. 2026-06-20에 다음에서 검색함: https://scholargate.app/ko/compare