Compara mètodes

	Model Estructural Marginal per a l'Avaluació de Polítiques	Avaluació d'Impact Contrafactual (AIC)
Camp	Inferència causal	Inferència causal
Família	Regression model	Regression model
Any d'origen	2000	1970s–2000s
Autor original	James M. Robins, Miguel A. Hernan, Babette Brumback	Heckman, Imbens, Rubin, and the program evaluation literature
Tipus	Causal inference / weighted regression	Causal inference / program evaluation
Font seminal	Robins, J. M., Hernan, M. A., & Brumback, B. (2000). Marginal structural models and causal inference in epidemiology. Epidemiology, 11(5), 550–560.	Heckman, J. J., & Vytlacil, E. J. (2007). Econometric evaluation of social programs, Part I: Causal models, structural models and econometric policy evaluation. Handbook of Econometrics, 6B, 4779-4874.
Àlies	MSM for policy evaluation, policy MSM, causal MSM, structural policy weighting model	CIE, counterfactual evaluation, counterfactual policy evaluation, impact evaluation
Relacionats	6	5
Resum	A Policy Evaluation Marginal Structural Model (MSM) is a causal inference framework that estimates the population-average effect of a policy by using inverse probability weighting to create a pseudo-population in which treatment assignment is independent of measured confounders, enabling unbiased comparison of potential outcomes under different policy scenarios from observational data.	Counterfactual Impact Evaluation is a family of causal methods that estimates the effect of an intervention by comparing what actually happened to participants with what would have happened had the intervention not taken place. Formalised in the Rubin Causal Model and extended by Heckman, Imbens and others, CIE underlies most modern program and policy evaluation practice.