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| 순서형 측정 불변성 검증× | 순서형 확인적 요인 분석× | |
|---|---|---|
| 분야 | 심리측정학 | 심리측정학 |
| 계열 | Latent structure | Latent structure |
| 기원 연도≠ | 1984–2011 | 1984 |
| 창시자≠ | Roger Millsap; Bengt Muthén | Bengt O. Muthén |
| 유형≠ | Multi-group model comparison | Latent variable / structural |
| 원전≠ | Millsap, R. E. (2011). Statistical Approaches to Measurement Invariance. Routledge. ISBN: 978-1848728936 | Flora, 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 ↗ |
| 별칭 | ordinal MI, measurement invariance for ordinal data, ordinal CFA invariance, categorical measurement invariance | CFA for ordinal data, polychoric CFA, WLSMV CFA, categorical CFA |
| 관련≠ | 6 | 5 |
| 요약≠ | 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. | 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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