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| ロバスト調整効果分析× | モデレーション(相互作用)分析× | |
|---|---|---|
| 分野≠ | 統計学 | 因果推論 |
| 系統≠ | Latent structure | Regression model |
| 提唱年≠ | 2007 | 2018 |
| 提唱者≠ | Hayes & Cai; Wilcox | Aiken & West (1991); Hayes (PROCESS, 2018) |
| 種類≠ | Robust regression-based interaction test | Linear regression with interaction term |
| 原典≠ | 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 |
| 別名 | robust interaction analysis, robust moderated regression, HC-corrected moderation, outlier-resistant interaction testing | interaction analysis, moderated regression, simple moderation, Düzenleyici Değişken Analizi (Moderation / İnteraksiyon) |
| 関連 | 5 | 5 |
| 概要≠ | 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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