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Marginales strukturelles Modell zur Politikbewertung×Gegenfactual-basierte Kausalanalyse (CIE)×
FachgebietKausale InferenzKausale Inferenz
FamilieRegression modelRegression model
Entstehungsjahr20001970s–2000s
UrheberJames M. Robins, Miguel A. Hernan, Babette BrumbackHeckman, Imbens, Rubin, and the program evaluation literature
TypCausal inference / weighted regressionCausal inference / program evaluation
Wegweisende QuelleRobins, J. M., Hernan, M. A., & Brumback, B. (2000). Marginal structural models and causal inference in epidemiology. Epidemiology, 11(5), 550–560. DOI ↗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. DOI ↗
AliasnamenMSM for policy evaluation, policy MSM, causal MSM, structural policy weighting modelCIE, counterfactual evaluation, counterfactual policy evaluation, impact evaluation
Verwandt65
ZusammenfassungA 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.
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ScholarGateMethoden vergleichen: Policy Evaluation Marginal Structural Model · Counterfactual Impact Evaluation. Abgerufen am 2026-06-18 von https://scholargate.app/de/compare