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Робусни Маргинални Структурни Модел×Model marginalnih strukturalnih podataka sa panelom (MSM)×
OblastKauzalno zaključivanjeKauzalno zaključivanje
PorodicaRegression modelRegression model
Godina nastanka2000–20042000
TvoracRobins, Hernán & Brumback; robustness extensions by Scharfstein, Rotnitzky, Lunceford & DavidianJames M. Robins, Miguel A. Hernan, Babette Brumback
TipCausal inference / weighted regressionCausal model for time-varying treatments
Temeljni izvorRobins, J. M., Hernán, M. A., & Brumback, B. (2000). Marginal structural models and causal inference in epidemiology. Epidemiology, 11(5), 550-560. DOI ↗Robins, J. M., Hernan, M. A., & Brumback, B. (2000). Marginal structural models and causal inference in epidemiology. Epidemiology, 11(5), 550-560. DOI ↗
Drugi nazivirobust MSM, doubly-robust MSM, sandwich-SE MSM, robust IPTW marginal structural modelMSM panel, longitudinal MSM, panel MSM, time-varying treatment MSM
Srodne65
SažetakRobust Marginal Structural Models (robust MSMs) extend the standard MSM framework — which uses inverse probability of treatment weighting to handle time-varying confounding — by pairing IPTW estimation with sandwich (robust) standard errors or doubly-robust estimators. This combination yields valid causal estimates and reliable inference even when the outcome regression model is mildly misspecified or weights are moderately variable.A panel data marginal structural model (MSM) uses inverse probability of treatment weighting (IPTW) across multiple time periods to estimate the causal effect of a time-varying treatment, while appropriately adjusting for time-varying confounders that are themselves affected by prior treatment — a bias source that conventional regression cannot handle.
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ScholarGateUporedite metode: Robust Marginal Structural Model · Panel Data Marginal Structural Model. Preuzeto 2026-06-15 sa https://scholargate.app/sr/compare