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| 방향성 비순환 그래프(DAG)를 이용한 인과 관계 식별(do-calculus)× | 매개 분석× | |
|---|---|---|
| 분야≠ | 인과추론 | 통계학 |
| 계열≠ | Regression model | Hypothesis test |
| 기원 연도≠ | 2009 | 1986 |
| 창시자≠ | Judea Pearl | Baron & Kenny |
| 유형≠ | Causal identification framework | Indirect effects / path test |
| 원전≠ | Pearl, J. (2009). Causality: Models, Reasoning, and Inference (2nd ed.). Cambridge University Press. ISBN: 978-0521895606 | 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 | do-calculus, backdoor adjustment, Pearl causal identification, DAG ile Nedensel Tanımlama (do-calculus) | indirect effects analysis, path-based mediation, PROCESS macro mediation, Aracılık Analizi (Mediation / PROCESS) |
| 관련 | 5 | 5 |
| 요약≠ | DAG causal identification is a framework, developed by Judea Pearl (2009), that encodes causal assumptions as a directed acyclic graph and uses the do-calculus rules to determine whether and how a causal effect can be identified from observational data. It systematically handles confounders, instrumental variables, and backdoor paths. | 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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