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| Ecological Inference× | 인과적 매개 분석 (자연 직접 효과 및 간접 효과)× | |
|---|---|---|
| 분야≠ | Political Science | 인과추론 |
| 계열 | Regression model | Regression model |
| 기원 연도≠ | 1997 | 2010 |
| 창시자≠ | Leo Goodman (ecological regression); Gary King (statistical EI solution) | Pearl (2001); general framework by Imai, Keele & Tingley (2010) |
| 유형≠ | Aggregate-data model inferring individual-level rates from grouped totals | Counterfactual causal decomposition |
| 원전≠ | King, G. (1997). A Solution to the Ecological Inference Problem: Reconstructing Individual Behavior from Aggregate Data. Princeton: Princeton University Press. ISBN: 9780691012414 | Pearl, J. (2001). Direct and Indirect Effects. In Proceedings of the Seventeenth Conference on Uncertainty in Artificial Intelligence (UAI), 411-420. link ↗ |
| 별칭≠ | EI, Ecological regression, King's ecological inference, Aggregate-to-individual inference | natural direct effect, natural indirect effect, NDE / NIE decomposition, counterfactual mediation |
| 관련 | 5 | 5 |
| 요약≠ | Ecological inference is the problem of learning about individual behavior — such as how Black and white voters cast their ballots — when only aggregate data are available, like precinct-level turnout and racial composition. Because individual-level data are missing, the within-group rates are not directly observed; ecological inference recovers them by combining the deterministic accounting constraints that each precinct must satisfy with a statistical model of how the unobserved rates vary across precincts. Gary King's 1997 solution unified the deterministic method of bounds with Leo Goodman's classic ecological regression, sharply reducing the long-standing risk of the ecological fallacy. | 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. |
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