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Kontrafaktualna evaluacija učinka (CIE)×Uparivanje prema ocjeni sklonosti×
PodručjeUzročno zaključivanjeIstraživačka statistika
ObiteljRegression modelProcess / pipeline
Godina nastanka1970s–2000s1983
TvoracHeckman, Imbens, Rubin, and the program evaluation literaturePaul Rosenbaum and Donald Rubin
VrstaCausal inference / program evaluationMethod
Temeljni izvorHeckman, 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 ↗Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41–55. DOI ↗
Drugi naziviCIE, counterfactual evaluation, counterfactual policy evaluation, impact evaluationPSM, propensity score weighting, covariate balance
Srodne53
SažetakCounterfactual 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.Propensity score matching (PSM) is a method for reducing confounding bias in observational studies by balancing baseline characteristics between treatment groups, simulating randomization. Developed by Rosenbaum and Rubin (1983), it estimates the probability of receiving treatment given observed covariates, then matches or weights treated and control individuals with similar treatment probabilities. Widely used in medicine, epidemiology, and policy evaluation when randomized trials are infeasible or unethical, enabling estimation of treatment effects while controlling for selection bias.
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ScholarGateUsporedite metode: Counterfactual Impact Evaluation · Propensity Score Matching. Preuzeto 2026-06-19 s https://scholargate.app/hr/compare