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| 教育研究中的模糊断点回归设计× | 倾向得分匹配× | |
|---|---|---|
| 领域≠ | 因果推断 | 研究统计学 |
| 方法族≠ | Regression model | Process / pipeline |
| 起源年份≠ | Late 1990s–2000s | 1983 |
| 提出者≠ | Imbens & Lemieux (2008); applied in education by Jacob & Lefgren (2004) and Angrist & Lavy (1999) | Paul Rosenbaum and Donald Rubin |
| 类型≠ | Quasi-experimental / causal inference | Method |
| 开创性文献≠ | Imbens, G. W., & Lemieux, T. (2008). Regression discontinuity designs: A guide to practice. Journal of Econometrics, 142(2), 615-635. 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 ↗ |
| 别名≠ | Fuzzy RDD, Fuzzy RD, Imperfect RDD, Non-sharp RD | PSM, propensity score weighting, covariate balance |
| 相关≠ | 4 | 3 |
| 摘要≠ | Fuzzy Regression Discontinuity Design (Fuzzy RDD) is a quasi-experimental causal method that exploits a known score threshold — such as a test cutoff — to estimate the effect of a program or intervention when assignment is imperfect. Widely used in education research to evaluate summer school, remedial programs, scholarships, and class-size rules, it uses two-stage least squares to recover a local average treatment effect for students near the threshold. | 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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