Compara mètodes

	Ecological Inference	Anàlisi de mediació causal (efectes directes i indirectes naturals)
Camp	Political Science	Inferència causal
Família	Regression model	Regression model
Any d'origen	1997	2010
Autor original	Leo Goodman (ecological regression); Gary King (statistical EI solution)	Pearl (2001); general framework by Imai, Keele & Tingley (2010)
Tipus	Aggregate-data model inferring individual-level rates from grouped totals	Counterfactual causal decomposition
Font seminal	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.
Àlies	EI, Ecological regression, King's ecological inference, Aggregate-to-individual inference	natural direct effect, natural indirect effect, NDE / NIE decomposition, counterfactual mediation
Relacionats	5	5
Resum	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.