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مدل ساختاری حاشیه‌ای اثر درمان ناهمگن (HTE-MSM)×وزن‌دهی احتمال معکوسِ دریافتِ درمان (IPW / IPTW)×
حوزهاستنتاج علّیاستنتاج علّی
خانوادهRegression modelRegression model
سال پیدایش2000–2010s2000
پدیدآورRobins, Hernan & Brumback (foundational MSM framework, 2000); heterogeneous-effect extensions developed throughout 2000s–2010sRobins, Hernán & Brumback
نوعCausal inference / weighted regression with effect modificationCausal inference weighting estimator
منبع بنیادینRobins, 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 ↗
نام‌های دیگرHTE-MSM, heterogeneous MSM, subgroup MSM, effect-modified marginal structural modelIPW, IPTW, inverse probability of treatment weighting, marginal structural model weighting
مرتبط55
خلاصهThe 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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  3. PUBLISHED

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ScholarGateمقایسهٔ روش‌ها: Heterogeneous Treatment Effect Marginal Structural Model · Inverse Probability Weighting. بازیابی‌شده در 2026-06-18 از https://scholargate.app/fa/compare