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| Đánh giá Tác động Phản thực tế trong Nghiên cứu Giáo dục× | Ghép cặp điểm xu hướng× | |
|---|---|---|
| Lĩnh vực≠ | Suy luận nhân quả | Thống kê nghiên cứu |
| Họ≠ | Regression model | Process / pipeline |
| Năm ra đời≠ | 2000s–2010s | 1983 |
| Người khởi xướng≠ | Blundell & Costa Dias; formalized for EU education policy by the European Commission Joint Research Centre | Paul Rosenbaum and Donald Rubin |
| Loại≠ | Quasi-experimental causal inference framework | Method |
| Công trình gốc≠ | Blundell, R., & Costa Dias, M. (2002). Alternative approaches to evaluation in empirical microeconomics. Portuguese Economic Journal, 1(2), 91-115. 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 khác≠ | CIE in education, counterfactual program evaluation, causal impact evaluation, education policy impact evaluation | PSM, propensity score weighting, covariate balance |
| Liên quan≠ | 5 | 3 |
| Tóm tắt≠ | Counterfactual impact evaluation (CIE) is the systematic application of causal inference designs — such as difference-in-differences, regression discontinuity, matching, and instrumental variables — to measure the genuine effect of education programs, policies, or interventions by constructing a credible counterfactual: what would have happened to participants had they not been treated. | 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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