Causal Mediation Analysis in Politics
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?'
Kilderegister
Siteringer kopiert ordrett fra metodens kilderegister. Ingen påstandsnivåverifisering er underforstått fra dem.
- Imai, K., Keele, L., & Tingley, D. (2010). A General Approach to Causal Mediation Analysis. Psychological Methods, 15(4), 309–334. · DOI 10.1037/a0020761
- Imai, K., Keele, L., Tingley, D., & Yamamoto, T. (2011). Unpacking the Black Box of Causality: Learning about Causal Mechanisms from Experimental and Observational Studies. American Political Science Review, 105(4), 765–789. · DOI 10.1017/S0003055411000414
Kuraterte påstander
Påstander lagret i bevishovedboken, hver med sin egen vurdering.
Denne visningen finner ikke opp en påstandsvurdering når hovedboken ikke har noen.
Relaterte metoder
Generert fra metodegrafen og vist som maskinforslåtte relasjoner – ingen bevispåstand er underforstått.