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| 패널 데이터 성향 점수 가중치 (panel PSW)× | 성향 점수 가중치 (PSW / IPW)× | |
|---|---|---|
| 분야 | 인과추론 | 인과추론 |
| 계열 | Regression model | Regression model |
| 기원 연도≠ | 2000-2003 | 1983 (propensity score); 2003 (efficient IPW estimator) |
| 창시자≠ | Hirano, Imbens & Ridder; Robins, Hernan & Brumback | Rosenbaum & Rubin (propensity score); Hirano, Imbens & Ridder (efficient weighting) |
| 유형≠ | Causal inference / panel weighting | Causal inference / reweighting |
| 원전≠ | Hirano, K., Imbens, G. W., & Ridder, G. (2003). Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score. Econometrica, 71(4), 1161-1189. 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 | panel PSW, panel IPW, longitudinal propensity score weighting, panel inverse probability weighting | PSW, inverse probability weighting, IPW, propensity-based weighting |
| 관련≠ | 5 | 6 |
| 요약≠ | Panel Data Propensity Score Weighting (panel PSW) extends inverse probability weighting to longitudinal settings where the same units are observed across multiple time periods. It reweights observations by the inverse of each unit's time-varying probability of receiving treatment, creating a pseudo-population in which treatment is balanced on observed covariates at each period, and then estimates causal effects from repeated-measures data. | 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). |
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