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Гетерогенная модель предельного структурного эффекта воздействия (HTE-MSM)×Взвешивание на основе оценки склонности (PSW / IPW)×
ОбластьПричинно-следственный выводПричинно-следственный вывод
СемействоRegression modelRegression model
Год появления2000–2010s1983 (propensity score); 2003 (efficient IPW estimator)
Автор методаRobins, Hernan & Brumback (foundational MSM framework, 2000); heterogeneous-effect extensions developed throughout 2000s–2010sRosenbaum & Rubin (propensity score); Hirano, Imbens & Ridder (efficient weighting)
ТипCausal inference / weighted regression with effect modificationCausal inference / reweighting
Основополагающий источникRobins, J. M., Hernan, M. A., & Brumback, B. (2000). Marginal structural models and causal inference in epidemiology. Epidemiology, 11(5), 550-560. 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 названияHTE-MSM, heterogeneous MSM, subgroup MSM, effect-modified marginal structural modelPSW, inverse probability weighting, IPW, propensity-based weighting
Связанные56
СводкаThe Heterogeneous Treatment Effect Marginal Structural Model extends the classic MSM framework of Robins, Hernan, and Brumback to estimate how treatment effects vary across subgroups or individual-level moderators. By weighting observations with inverse probability of treatment weights (IPTW) and interacting the treatment with effect modifiers in the weighted outcome model, the approach produces subgroup-specific or continuous causal effect estimates from observational 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).
ScholarGateНабор данных
  1. v1
  2. 2 Источники
  3. PUBLISHED
  1. v1
  2. 2 Источники
  3. PUBLISHED

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ScholarGateСравнение методов: Heterogeneous Treatment Effect Marginal Structural Model · Propensity Score Weighting. Получено 2026-06-19 из https://scholargate.app/ru/compare