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विषम उपचार प्रभाव सीमांत संरचनात्मक मॉडल (HTE-MSM)×उपचार भारण की व्युत्क्रम प्रायिकता (IPW / IPTW)×
क्षेत्रकारणात्मक अनुमानकारणात्मक अनुमान
परिवारRegression modelRegression model
उद्भव वर्ष2000–2010s2000
प्रवर्तकRobins, Hernan & Brumback (foundational MSM framework, 2000); heterogeneous-effect extensions developed throughout 2000s–2010sRobins, Hernán & Brumback
प्रकारCausal inference / weighted regression with effect modificationCausal inference weighting estimator
मौलिक स्रोतRobins, 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 ↗
उपनामHTE-MSM, heterogeneous MSM, subgroup MSM, effect-modified marginal structural modelIPW, IPTW, inverse probability of treatment weighting, marginal structural model weighting
संबंधित55
सारांशThe 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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ScholarGateविधियों की तुलना करें: Heterogeneous Treatment Effect Marginal Structural Model · Inverse Probability Weighting. 2026-06-19 को यहाँ से प्राप्त https://scholargate.app/hi/compare