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Model marginalne strukture za panel podatke (MSM)×Uteživanje inverznom vjerojatnošću tretmana (IPW / IPTW)×
PodručjeUzročno zaključivanjeUzročno zaključivanje
ObiteljRegression modelRegression model
Godina nastanka20002000
TvoracJames M. Robins, Miguel A. Hernan, Babette BrumbackRobins, Hernán & Brumback
VrstaCausal model for time-varying treatmentsCausal inference weighting estimator
Temeljni izvorRobins, 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 ↗
Drugi naziviMSM panel, longitudinal MSM, panel MSM, time-varying treatment MSMIPW, IPTW, inverse probability of treatment weighting, marginal structural model weighting
Srodne55
SažetakA 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.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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ScholarGateUsporedite metode: Panel Data Marginal Structural Model · Inverse Probability Weighting. Preuzeto 2026-06-17 s https://scholargate.app/hr/compare