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| 교육 연구에서의 이중차분법× | 성향 점수 매칭× | |
|---|---|---|
| 분야≠ | 인과추론 | 연구 통계 |
| 계열≠ | Regression model | Process / pipeline |
| 기원 연도≠ | 1990s–2000s | 1983 |
| 창시자≠ | Dynarski, Card, Angrist, and colleagues — applied in education economics from the 1990s onward | Paul Rosenbaum and Donald Rubin |
| 유형≠ | Quasi-experimental causal inference | Method |
| 원전≠ | Dynarski, S. M. (2003). Does Aid Matter? Measuring the Effect of Student Aid on College Attendance and Completion. American Economic Review, 93(1), 279-288. 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 ↗ |
| 별칭≠ | DiD in education, education DiD, quasi-experimental education design, education policy DiD | PSM, propensity score weighting, covariate balance |
| 관련≠ | 5 | 3 |
| 요약≠ | Difference-in-Differences (DiD) in education research applies the classic quasi-experimental DiD estimator to evaluate education policies, programs, and reforms. Researchers compare changes in student, school, or district outcomes between a group exposed to an intervention and a comparable unexposed group across pre- and post-intervention periods, isolating policy effects from background trends. | 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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