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| 序数判别效度× | 序数确认因子分析 (序数 CFA)× | |
|---|---|---|
| 领域 | 心理测量学 | 心理测量学 |
| 方法族 | Latent structure | Latent structure |
| 起源年份≠ | 1959 (concept); 2000s–2010s (ordinal adaptations) | 1984 |
| 提出者≠ | Campbell & Fiske (discriminant validity concept); adapted for ordinal data by subsequent psychometricians | Bengt O. Muthén |
| 类型≠ | Validity assessment | Latent variable / structural |
| 开创性文献≠ | Campbell, D. T., & Fiske, D. W. (1959). Convergent and discriminant validation by the multitrait-multimethod matrix. Psychological Bulletin, 56(2), 81–105. DOI ↗ | 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 ↗ |
| 别名 | discriminant validity for ordinal data, polychoric discriminant validity, ordinal HTMT, ordinal AVE-based discriminant validity | CFA for ordinal data, polychoric CFA, WLSMV CFA, categorical CFA |
| 相关≠ | 6 | 5 |
| 摘要≠ | Ordinal discriminant validity assesses whether a latent construct measured by ordinal (Likert-type) items is empirically distinct from other constructs in the same instrument. It applies polychoric correlations and ordinal-appropriate factor loadings to standard discriminant validity criteria such as the Fornell-Larcker rule and the Heterotrait-Monotrait ratio (HTMT), ensuring that validity conclusions are not distorted by the non-continuous nature of ordered-response data. | 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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