ScholarGate
Ассистент

Сравнение методов

Просматривайте выбранные методы рядом; строки с различиями подсвечены.

Байесовская маргинальная структурная модель×Взвешивание на основе оценки склонности (PSW / IPW)×
ОбластьПричинно-следственный выводПричинно-следственный вывод
СемействоRegression modelRegression model
Год появления2015 (Bayesian extension); 2000 (MSM foundation)1983 (propensity score); 2003 (efficient IPW estimator)
Автор методаSaarela, Stephens, Moodie & Klein (Bayesian extension); Robins, Hernan & Brumback (original MSM)Rosenbaum & Rubin (propensity score); Hirano, Imbens & Ridder (efficient weighting)
ТипCausal inference / Bayesian weighted regressionCausal inference / reweighting
Основополагающий источникSaarela, O., Stephens, D. A., Moodie, E. E. M., & Klein, M. B. (2015). On Bayesian estimation of marginal structural models. Biometrics, 71(2), 279-288. 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 названияBayesian MSM, Bayesian MSM-IPW, Bayesian weighted structural model, Bayesian causal MSMPSW, inverse probability weighting, IPW, propensity-based weighting
Связанные66
СводкаBayesian Marginal Structural Model (Bayesian MSM) combines the causal identification power of inverse-probability-weighted marginal structural models with Bayesian posterior inference. Rather than relying on point estimates and asymptotic standard errors, it propagates uncertainty through a full posterior distribution over causal effect parameters, offering coherent uncertainty quantification for causal effects of time-varying treatments.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: Bayesian Marginal Structural Model · Propensity Score Weighting. Получено 2026-06-17 из https://scholargate.app/ru/compare