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| 강건한 조절 분석(Robust Moderation Analysis)× | 조절(상호작용) 분석× | |
|---|---|---|
| 분야≠ | 통계학 | 인과추론 |
| 계열≠ | Latent structure | Regression model |
| 기원 연도≠ | 2007 | 2018 |
| 창시자≠ | Hayes & Cai; Wilcox | Aiken & West (1991); Hayes (PROCESS, 2018) |
| 유형≠ | Robust regression-based interaction test | Linear regression with interaction term |
| 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 (2nd ed.). Guilford Press. ISBN: 978-1462534654 |
| 별칭 | robust interaction analysis, robust moderated regression, HC-corrected moderation, outlier-resistant interaction testing | interaction analysis, moderated regression, simple moderation, Düzenleyici Değişken Analizi (Moderation / İnteraksiyon) |
| 관련 | 5 | 5 |
| 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. | Moderation analysis tests whether the effect of a predictor X on an outcome Y changes with the level of a third variable W, the moderator. It is estimated within a regression framework through an interaction term X×W, popularised by Aiken & West (1991) and Hayes's PROCESS macro (2018). |
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