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순서형 측정 불변성 검증×순서형 확인적 요인 분석×
분야심리측정학심리측정학
계열Latent structureLatent structure
기원 연도1984–20111984
창시자Roger Millsap; Bengt MuthénBengt O. Muthén
유형Multi-group model comparisonLatent variable / structural
원전Millsap, R. E. (2011). Statistical Approaches to Measurement Invariance. Routledge. ISBN: 978-1848728936Flora, D. B. & Curran, P. J. (2004). An empirical evaluation of alternative methods of estimation for confirmatory factor analysis with ordinal data. Psychological Methods, 9(4), 466–491. DOI ↗
별칭ordinal MI, measurement invariance for ordinal data, ordinal CFA invariance, categorical measurement invarianceCFA for ordinal data, polychoric CFA, WLSMV CFA, categorical CFA
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.Ordinal confirmatory factor analysis (Ordinal CFA) tests a pre-specified factor structure when the observed indicators are ordinal — typically Likert-type survey items. By using polychoric correlations and robust estimators such as WLSMV, it avoids the bias that arises from treating categorical responses as continuous.
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