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| 교육 연구에서의 성향 점수 매칭× | 매칭 추정량× | |
|---|---|---|
| 분야 | 인과추론 | 인과추론 |
| 계열 | Regression model | Regression model |
| 기원 연도≠ | 1983 (foundational); education adoption widespread from late 1990s | 1973 |
| 창시자≠ | Rosenbaum & Rubin (1983); widely adopted in education research via Shadish, Cook & Campbell (2002) | Rubin (1973); large-sample theory by Abadie & Imbens (2006) |
| 유형≠ | Quasi-experimental / matching-based causal inference | Nonparametric matching / causal inference |
| 원전≠ | 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 ↗ | Abadie, A., & Imbens, G. W. (2006). Large Sample Properties of Matching Estimators for Average Treatment Effects. Econometrica, 74(1), 235-267. DOI ↗ |
| 별칭 | PSM in education, educational PSM, PSM for program evaluation in schools, propensity matching education | nearest-neighbor matching, NNM, matching on covariates, covariate matching |
| 관련≠ | 5 | 6 |
| 요약≠ | 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. | The matching estimator identifies the causal effect of a treatment by pairing each treated unit with one or more untreated units that have similar observed characteristics. Formalised by Rubin (1973) and given rigorous large-sample theory by Abadie and Imbens (2006), it constructs a credible control group from observational data without requiring a parametric model for the outcome. |
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