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異質的処置効果周辺構造モデル(HTE-MSM)×逆確率重み付け法 (IPW / IPTW)×
分野因果推論因果推論
系統Regression modelRegression model
提唱年2000–2010s2000
提唱者Robins, Hernan & Brumback (foundational MSM framework, 2000); heterogeneous-effect extensions developed throughout 2000s–2010sRobins, Hernán & Brumback
種類Causal inference / weighted regression with effect modificationCausal inference weighting estimator
原典Robins, J. M., Hernan, M. A., & Brumback, B. (2000). Marginal structural models and causal inference in epidemiology. Epidemiology, 11(5), 550-560. DOI ↗Robins, J. M., Hernán, M. A., & Brumback, B. (2000). Marginal Structural Models and Causal Inference in Epidemiology. Epidemiology, 11(5), 550-560. DOI ↗
別名HTE-MSM, heterogeneous MSM, subgroup MSM, effect-modified marginal structural modelIPW, IPTW, inverse probability of treatment weighting, marginal structural model weighting
関連55
概要The 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.Inverse Probability Weighting is a causal-inference method that assigns each observation a weight equal to the inverse of its probability of receiving the treatment it actually received. Introduced by Robins, Hernán and Brumback (2000) for marginal structural models, it builds a pseudo-population in which treatment is independent of measured confounders, balancing selection bias.
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ScholarGate手法を比較: Heterogeneous Treatment Effect Marginal Structural Model · Inverse Probability Weighting. 2026-06-19に以下より取得 https://scholargate.app/ja/compare