Comparer des méthodes

	Causal Mediation Analysis in Politics	Analyse causale de médiation (effets directs et indirects naturels)
Domaine	Political Science	Inférence causale
Famille	Regression model	Regression model
Année d'origine	2010	2010
Auteur d'origine	Imai, Keele, Tingley & Yamamoto (potential-outcomes causal mediation)	Pearl (2001); general framework by Imai, Keele & Tingley (2010)
Type	Causal-inference decomposition of a treatment effect into direct and indirect (mediated) components	Counterfactual causal decomposition
Source fondatrice	Imai, K., Keele, L., & Tingley, D. (2010). A General Approach to Causal Mediation Analysis. Psychological Methods, 15(4), 309–334.	Pearl, J. (2001). Direct and Indirect Effects. In Proceedings of the Seventeenth Conference on Uncertainty in Artificial Intelligence (UAI), 411-420.
Alias	Causal mediation, Mechanism analysis, Direct and indirect effects, Potential-outcomes mediation	natural direct effect, natural indirect effect, NDE / NIE decomposition, counterfactual mediation
Apparentées	5	5
Résumé	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?'	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.