방법 비교

	Causal Mediation Analysis in Politics	매개 분석
분야	Political Science	통계학
계열	Regression model	Hypothesis test
기원 연도	2010	1986
창시자	Imai, Keele, Tingley & Yamamoto (potential-outcomes causal mediation)	Baron & Kenny
유형	Causal-inference decomposition of a treatment effect into direct and indirect (mediated) components	Indirect effects / path test
원전	Imai, K., Keele, L., & Tingley, D. (2010). A General Approach to Causal Mediation Analysis. Psychological Methods, 15(4), 309–334.	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.
별칭	Causal mediation, Mechanism analysis, Direct and indirect effects, Potential-outcomes mediation	indirect effects analysis, path-based mediation, PROCESS macro mediation, Aracılık Analizi (Mediation / PROCESS)
관련	5	5
요약	Causal mediation analysis decomposes the effect of a treatment — often a randomized experimental manipulation, such as a campaign message or an information treatment — into the part transmitted through a specified intermediate variable, the mediator, and the part operating through all other pathways. Formalized in the potential-outcomes framework by Imai, Keele, Tingley, and Yamamoto, it defines the average causal mediation effect (ACME) and the average direct effect, makes explicit the sequential-ignorability assumption required to identify them, and supplies a sensitivity analysis for when that assumption fails. It lets political scientists move beyond 'does the treatment work?' to 'why does it work?'	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.