Uporedite metode

	Višeperiodna kontrafaktuelna evaluacija uticaja	Marginalni strukturni model (MSM)
Oblast	Kauzalno zaključivanje	Kauzalno zaključivanje
Porodica	Regression model	Regression model
Godina nastanka	2000s–2010s	2000
Tvorac	Developed through EU policy evaluation practice (European Commission); formalized by Lechner, Caliendo, and related econometricians	James M. Robins, Miguel A. Hernan, Babette Brumback
Tip	Causal inference / quasi-experimental evaluation	Causal model / semiparametric weighting
Temeljni izvor	Caliendo, M., & Kopeinig, S. (2008). Some Practical Guidance for the Implementation of Propensity Score Matching. Journal of Economic Surveys, 22(1), 31-72.	Robins, J. M., Hernan, M. A., & Brumback, B. (2000). Marginal structural models and causal inference in epidemiology. Epidemiology, 11(5), 550-560.
Drugi nazivi	multi-period CIE, longitudinal counterfactual evaluation, dynamic counterfactual impact evaluation, multi-wave CIE	MSM, MSM-IPTW, marginal structural Cox model, weighted structural model
Srodne	4	5
Sažetak	Multi-period Counterfactual Impact Evaluation (CIE) estimates the causal effect of a policy or program by constructing what would have happened to treated units across multiple time periods had they not been treated. Unlike single-period evaluations, it tracks treatment effects as they evolve over time, capturing dynamic, delayed, or fading impacts that a two-period comparison would miss.	A marginal structural model is a causal modeling framework designed to estimate the effect of a time-varying treatment in the presence of time-varying confounders that are themselves affected by prior treatment. By reweighting observations with inverse probability of treatment weights, MSMs create a pseudo-population in which confounding is eliminated, enabling unbiased estimation of causal treatment contrasts even when standard regression adjustments would fail.