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| ロバスト構造方程式モデリング× | ロバスト確証的因子分析× | |
|---|---|---|
| 分野 | 統計学 | 統計学 |
| 系統 | Latent structure | Latent structure |
| 提唱年≠ | 1994 | 1984–1994 |
| 提唱者≠ | Albert Satorra & Peter M. Bentler | Satorra & Bentler (robust SE/chi-square corrections); Browne (ADF estimator) |
| 種類≠ | Latent variable / path model with robust inference | Confirmatory latent variable model with robust estimation |
| 原典≠ | 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 (pp. 399–419). Sage. link ↗ | 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 ↗ |
| 別名 | Robust SEM, SEM with robust standard errors, Satorra-Bentler SEM, non-normal SEM | Robust CFA, CFA with robust standard errors, Satorra-Bentler CFA, non-normal CFA |
| 関連≠ | 5 | 6 |
| 概要≠ | Robust structural equation modeling (Robust SEM) applies the full SEM framework — simultaneous estimation of measurement and structural relations among latent variables — while using corrected test statistics and sandwich standard errors that remain valid when observed data depart from multivariate normality. The Satorra-Bentler scaled chi-square is the most widely used correction. | 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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