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| Phân tích nhân tố khám phá mạnh mẽ× | Phân tích nhân tố xác nhận mạnh mẽ× | |
|---|---|---|
| Lĩnh vực≠ | Trắc lượng tâm lý | Thống kê |
| Họ | Latent structure | Latent structure |
| Năm ra đời≠ | 2000–2003 | 1984–1994 |
| Người khởi xướng≠ | Pison, Rousseeuw, Filzmoser, and Croux; Yuan and Bentler (parallel streams) | Satorra & Bentler (robust SE/chi-square corrections); Browne (ADF estimator) |
| Loại≠ | Latent variable / dimension reduction (robust) | Confirmatory latent variable model with robust estimation |
| Công trình gốc≠ | Yuan, K.-H., & Bentler, P. M. (2000). Robust mean and covariance structure analysis through iteratively reweighted least squares. Psychometrika, 65(1), 43–58. DOI ↗ | Satorra, A. & Bentler, P. M. (1994). Corrections to test statistics and standard errors in covariance structure analysis. In A. von Eye & C. C. Clogg (Eds.), Latent variables analysis: Applications for developmental research (pp. 399–419). Sage. link ↗ |
| Tên gọi khác | robust EFA, robust factor analysis, outlier-resistant factor analysis, EFA with robust estimation | Robust CFA, CFA with robust standard errors, Satorra-Bentler CFA, non-normal CFA |
| Liên quan≠ | 4 | 6 |
| Tóm tắt≠ | Robust exploratory factor analysis discovers the latent factor structure of a set of items using estimation methods that are resistant to outliers and violations of multivariate normality. It applies the same measurement model as standard EFA but replaces classical covariance estimation with robust counterparts — such as minimum covariance determinant or iteratively reweighted least squares — so that a small fraction of atypical cases cannot distort the recovered factor loadings. | Robust confirmatory factor analysis fits a pre-specified factor structure to observed data while correcting standard errors and goodness-of-fit statistics for violations of multivariate normality. It is the preferred variant of CFA whenever Likert-type, skewed, or kurtotic indicators make the classical normal-theory estimator unreliable. |
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