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| تحليل التعديل القوي (Robust Moderation Analysis)× | تحليل المسار القوي× | |
|---|---|---|
| المجال | الإحصاء | الإحصاء |
| العائلة | Latent structure | Latent structure |
| سنة النشأة≠ | 2007 | 1998 |
| صاحب الطريقة≠ | Hayes & Cai; Wilcox | Yuan & Bentler (robust SEM/path framework); Huber (M-estimation foundation) |
| النوع≠ | Robust regression-based interaction test | Causal path modeling with robust estimation |
| المصدر التأسيسي≠ | 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 ↗ |
| الأسماء البديلة | 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 |
| ذات صلة≠ | 5 | 6 |
| الملخص≠ | 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. |
| ScholarGateمجموعة البيانات ↗ |
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