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| 인과적 매개 분석 (자연 직접 효과 및 간접 효과)× | 매개 분석× | |
|---|---|---|
| 분야≠ | 인과추론 | 통계학 |
| 계열≠ | Regression model | Hypothesis test |
| 기원 연도≠ | 2010 | 1986 |
| 창시자≠ | Pearl (2001); general framework by Imai, Keele & Tingley (2010) | Baron & Kenny |
| 유형≠ | Counterfactual causal decomposition | Indirect effects / path test |
| 원전≠ | Pearl, J. (2001). Direct and Indirect Effects. In Proceedings of the Seventeenth Conference on Uncertainty in Artificial Intelligence (UAI), 411-420. link ↗ | Baron, R. M. & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research. Journal of Personality and Social Psychology, 51(6), 1173–1182. link ↗ |
| 별칭≠ | natural direct effect, natural indirect effect, NDE / NIE decomposition, counterfactual mediation | indirect effects analysis, path-based mediation, PROCESS macro mediation, Aracılık Analizi (Mediation / PROCESS) |
| 관련 | 5 | 5 |
| 요약≠ | 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. | Mediation analysis is a statistical procedure that tests whether the effect of an independent variable X on an outcome Y operates wholly or partly through a third variable M, called the mediator. Formalised by Baron and Kenny in 1986, it decomposes the total effect of X on Y into a direct path (c′) and an indirect path (a × b), quantifying how much of the relationship is carried by the mediating mechanism. |
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