ScholarGate
Ассистент

Сравнение методов

Просматривайте выбранные методы рядом; строки с различиями подсвечены.

Робастное взвешивание на основе оценки склонности×Взвешивание на основе оценки склонности (PSW / IPW)×
ОбластьПричинно-следственный выводПричинно-следственный вывод
СемействоRegression modelRegression model
Год появления1994–20191983 (propensity score); 2003 (efficient IPW estimator)
Автор методаRobins, Rotnitzky, & Zhao (foundational augmented IPW); Zhao, Small, & Bhattacharya (sensitivity-robust IPW)Rosenbaum & Rubin (propensity score); Hirano, Imbens & Ridder (efficient weighting)
ТипRobust causal weighting estimatorCausal inference / reweighting
Основополагающий источникRobins, 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 ↗
Другие названияrobust PSW, robust IPW, robustness-augmented propensity score weighting, misspecification-robust weightingPSW, inverse probability weighting, IPW, propensity-based weighting
Связанные66
СводкаRobust 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).
ScholarGateНабор данных
  1. v1
  2. 2 Источники
  3. PUBLISHED
  1. v1
  2. 2 Источники
  3. PUBLISHED

Перейти к поиску Скачать слайды

ScholarGateСравнение методов: Robust Propensity Score Weighting · Propensity Score Weighting. Получено 2026-06-19 из https://scholargate.app/ru/compare