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교육 연구에서의 성향 점수 매칭×역확률 가중치 (Inverse Probability Weighting, IPW / IPTW)×
분야인과추론인과추론
계열Regression modelRegression model
기원 연도1983 (foundational); education adoption widespread from late 1990s2000
창시자Rosenbaum & Rubin (1983); widely adopted in education research via Shadish, Cook & Campbell (2002)Robins, Hernán & Brumback
유형Quasi-experimental / matching-based causal inferenceCausal inference weighting estimator
원전Rosenbaum, 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 ↗Robins, J. M., Hernán, M. A., & Brumback, B. (2000). Marginal Structural Models and Causal Inference in Epidemiology. Epidemiology, 11(5), 550-560. DOI ↗
별칭PSM in education, educational PSM, PSM for program evaluation in schools, propensity matching educationIPW, IPTW, inverse probability of treatment weighting, marginal structural model weighting
관련55
요약Propensity 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.Inverse Probability Weighting is a causal-inference method that assigns each observation a weight equal to the inverse of its probability of receiving the treatment it actually received. Introduced by Robins, Hernán and Brumback (2000) for marginal structural models, it builds a pseudo-population in which treatment is independent of measured confounders, balancing selection bias.
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ScholarGate방법 비교: Propensity Score Matching in Education Research · Inverse Probability Weighting. 2026-06-20에 다음에서 검색함: https://scholargate.app/ko/compare