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| モデレーション（相互作用）分析× | 因果媒介分析（自然直接効果および自然間接効果）× | |
|---|---|---|
| 分野 | 因果推論 | 因果推論 |
| 系統 | Regression model | Regression model |
| 提唱年≠ | 2018 | 2010 |
| 提唱者≠ | Aiken & West (1991); Hayes (PROCESS, 2018) | Pearl (2001); general framework by Imai, Keele & Tingley (2010) |
| 種類≠ | Linear regression with interaction term | Counterfactual causal decomposition |
| 原典≠ | Hayes, A. F. (2018). Introduction to Mediation, Moderation, and Conditional Process Analysis (2nd ed.). Guilford Press. ISBN: 978-1462534654 | Pearl, J. (2001). Direct and Indirect Effects. In Proceedings of the Seventeenth Conference on Uncertainty in Artificial Intelligence (UAI), 411-420. link ↗ |
| 別名≠ | interaction analysis, moderated regression, simple moderation, Düzenleyici Değişken Analizi (Moderation / İnteraksiyon) | natural direct effect, natural indirect effect, NDE / NIE decomposition, counterfactual mediation |
| 関連 | 5 | 5 |
| 概要≠ | 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). | Causal mediation analysis is a counterfactual framework that splits a treatment's total effect into a Natural Direct Effect (NDE) and a Natural Indirect Effect (NIE) that runs through a mediator. The modern general approach was formalised by Pearl (2001) and Imai, Keele and Tingley (2010), giving the decomposition a precise causal interpretation. |
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