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Đánh giá Tác động Phản thực tế (CIE)×Ghép cặp điểm xu hướng×
Lĩnh vựcSuy luận nhân quảThống kê nghiên cứu
HọRegression modelProcess / pipeline
Năm ra đời1970s–2000s1983
Người khởi xướngHeckman, Imbens, Rubin, and the program evaluation literaturePaul Rosenbaum and Donald Rubin
LoạiCausal inference / program evaluationMethod
Công trình gốcHeckman, 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 ↗
Tên gọi khácCIE, counterfactual evaluation, counterfactual policy evaluation, impact evaluationPSM, propensity score weighting, covariate balance
Liên quan53
Tóm tắtCounterfactual 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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ScholarGateSo sánh phương pháp: Counterfactual Impact Evaluation · Propensity Score Matching. Truy cập ngày 2026-06-19 từ https://scholargate.app/vi/compare