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| 강건한 조절 분석(Robust Moderation Analysis)× | 조절된 매개 분석× | |
|---|---|---|
| 분야 | 통계학 | 통계학 |
| 계열 | Latent structure | Latent structure |
| 기원 연도 | 2007 | 2007 |
| 창시자≠ | Hayes & Cai; Wilcox | Preacher, Rucker & Hayes |
| 유형≠ | Robust regression-based interaction test | Conditional process model |
| 원전≠ | 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 ↗ | Hayes, A. F. (2018). Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach (2nd ed.). Guilford Press. ISBN: 978-1462534654 |
| 별칭 | robust interaction analysis, robust moderated regression, HC-corrected moderation, outlier-resistant interaction testing | conditional process analysis, moderated mediation model, first-stage moderated mediation, second-stage moderated mediation |
| 관련≠ | 5 | 4 |
| 요약≠ | 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. | Moderated mediation tests whether the indirect effect of an independent variable on an outcome — transmitted through a mediator — differs in strength depending on the level of a moderator variable. It answers the question: for whom, or under what conditions, does the mediated pathway operate most strongly? |
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