方法对比

	教育研究中的倾向得分匹配	倾向得分加权法 (PSW / IPW)
领域	因果推断	因果推断
方法族	Regression model	Regression model
起源年份	1983 (foundational); education adoption widespread from late 1990s	1983 (propensity score); 2003 (efficient IPW estimator)
提出者	Rosenbaum & Rubin (1983); widely adopted in education research via Shadish, Cook & Campbell (2002)	Rosenbaum & Rubin (propensity score); Hirano, Imbens & Ridder (efficient weighting)
类型	Quasi-experimental / matching-based causal inference	Causal inference / reweighting
开创性文献	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.	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.
别名	PSM in education, educational PSM, PSM for program evaluation in schools, propensity matching education	PSW, inverse probability weighting, IPW, propensity-based weighting
相关	5	6
摘要	Propensity Score Matching (PSM) in education research is a quasi-experimental technique that creates comparable treatment and control groups from observational student, teacher, or school data. By balancing groups on observed background characteristics, it enables credible causal estimates of educational interventions — such as tutoring programs, school choice policies, or teacher professional development — when random assignment is infeasible.	Propensity score weighting is a causal-inference method that reweights observations so that the covariate distributions of treated and untreated units look exchangeable, enabling unbiased estimation of average treatment effects from observational data. Each unit receives a weight that is the inverse of its probability of receiving the treatment it actually received — a strategy formalised by Rosenbaum and Rubin (1983) and given its efficient semiparametric form by Hirano, Imbens and Ridder (2003).