เปรียบเทียบวิธี
ดูวิธีที่เลือกเทียบกันแบบเคียงข้าง แถวที่ต่างกันจะถูกเน้นไว้
| การถ่วงน้ำหนักคะแนนความโน้มเอียงแบบทนทาน× | การถ่วงน้ำหนักด้วยคะแนนแนวโน้ม (Propensity Score Weighting - PSW / IPW)× | |
|---|---|---|
| สาขาวิชา | การอนุมานเชิงสาเหตุ | การอนุมานเชิงสาเหตุ |
| ตระกูล | Regression model | Regression model |
| ปีกำเนิด≠ | 1994–2019 | 1983 (propensity score); 2003 (efficient IPW estimator) |
| ผู้ริเริ่ม≠ | Robins, Rotnitzky, & Zhao (foundational augmented IPW); Zhao, Small, & Bhattacharya (sensitivity-robust IPW) | Rosenbaum & Rubin (propensity score); Hirano, Imbens & Ridder (efficient weighting) |
| ประเภท≠ | Robust causal weighting estimator | Causal inference / reweighting |
| แหล่งต้นตำรับ≠ | Robins, J. M., Rotnitzky, A., & Zhao, L. P. (1994). Estimation of regression coefficients when some regressors are not always observed. Journal of the American Statistical Association, 89(427), 846-866. 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 ↗ |
| ชื่อเรียกอื่น | robust PSW, robust IPW, robustness-augmented propensity score weighting, misspecification-robust weighting | PSW, inverse probability weighting, IPW, propensity-based weighting |
| ที่เกี่ยวข้อง | 6 | 6 |
| สรุป≠ | Robust Propensity Score Weighting extends standard inverse probability weighting by incorporating safeguards against misspecification of the propensity score model and extreme weights. It combines techniques such as weight trimming, overlap weighting, or augmented outcome models to ensure that causal effect estimates remain reliable even when the propensity score model is imperfectly specified. | 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). |
| ScholarGateชุดข้อมูล ↗ |
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