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| Phân tích tương quan mạnh mẽ× | Phân tích đường dẫn mạnh mẽ× | |
|---|---|---|
| Lĩnh vực | Thống kê | Thống kê |
| Họ | Latent structure | Latent structure |
| Năm ra đời≠ | 2007 | 1998 |
| Người khởi xướng≠ | Hayes & Cai; Wilcox | Yuan & Bentler (robust SEM/path framework); Huber (M-estimation foundation) |
| Loại≠ | Robust regression-based interaction test | Causal path modeling with robust estimation |
| Công trình gốc≠ | Hayes, A. F. & Cai, L. (2007). Using heteroscedasticity-consistent standard error estimators in OLS regression: An introduction and software implementation. Behavior Research Methods, 39(4), 709–722. DOI ↗ | Yuan, K.-H. & Bentler, P. M. (1998). Robust mean and covariance structure analysis. British Journal of Mathematical and Statistical Psychology, 51(1), 63–88. DOI ↗ |
| Tên gọi khác | robust interaction analysis, robust moderated regression, HC-corrected moderation, outlier-resistant interaction testing | robust PA, path analysis with robust standard errors, robust causal path modeling, robust structural path modeling |
| Liên quan≠ | 5 | 6 |
| Tóm tắt≠ | Robust moderation analysis tests whether the effect of a predictor on an outcome depends on the level of a moderator variable, using estimation methods that remain valid under non-normality, heteroscedasticity, or the presence of influential outliers. It is the preferred approach when standard ordinary least squares assumptions cannot be trusted. | Robust path analysis applies robust estimation — such as sandwich standard errors or M-estimation — to path models that specify directed causal relationships among observed variables. It preserves valid inference about path coefficients and indirect effects when data violate normality, contain outliers, or exhibit heteroscedasticity that would distort conventional standard errors. |
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