Salīdzināt metodes

	Marginalā strukturālā modelēšana politikas novērtēšanai	Kontrafaktiskās ietekmes novērtēšana (CIE)
Nozare	Cēloņsakarību secināšana	Cēloņsakarību secināšana
Saime	Regression model	Regression model
Izcelsmes gads	2000	1970s–2000s
Autors	James M. Robins, Miguel A. Hernan, Babette Brumback	Heckman, Imbens, Rubin, and the program evaluation literature
Tips	Causal inference / weighted regression	Causal inference / program evaluation
Pirmavots	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.
Citi nosaukumi	MSM for policy evaluation, policy MSM, causal MSM, structural policy weighting model	CIE, counterfactual evaluation, counterfactual policy evaluation, impact evaluation
Saistītās	6	5
Kopsavilkums	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.