方法对比
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| 调节（交互）分析× | 有条件过程分析（有调节的中介）× | |
|---|---|---|
| 领域 | 因果推断 | 因果推断 |
| 方法族 | Regression model | Regression model |
| 起源年份 | 2018 | 2018 |
| 提出者≠ | Aiken & West (1991); Hayes (PROCESS, 2018) | Andrew F. Hayes (PROCESS framework); Preacher, Rucker & Hayes (moderated mediation) |
| 类型≠ | Linear regression with interaction term | Regression-based conditional process model |
| 开创性文献≠ | Hayes, A. F. (2018). Introduction to Mediation, Moderation, and Conditional Process Analysis (2nd ed.). Guilford Press. ISBN: 978-1462534654 | Hayes, A. F. (2018). Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach (2nd ed.). The Guilford Press. ISBN: 978-1462534654 |
| 别名≠ | interaction analysis, moderated regression, simple moderation, Düzenleyici Değişken Analizi (Moderation / İnteraksiyon) | moderated mediation, moderated mediation analysis, PROCESS model, Hayes PROCESS conditional process model |
| 相关 | 5 | 5 |
| 摘要≠ | 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). | Conditional process analysis is Andrew F. Hayes's regression-based PROCESS framework (2018) that combines mediation and moderation in a single model, testing how an indirect effect changes across levels of a moderator. It quantifies conditional indirect and conditional direct effects and tests them with bootstrap confidence intervals. |
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