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Μοντέλο Οριακών Δομών για Αξιολόγηση Πολιτικής×Αντίστροφη Πιθανότητα Στάθμισης Θεραπείας (IPW / IPTW)×
ΠεδίοΑιτιακή ΣυμπερασματολογίαΑιτιακή Συμπερασματολογία
ΟικογένειαRegression modelRegression model
Έτος προέλευσης20002000
ΔημιουργόςJames M. Robins, Miguel A. Hernan, Babette BrumbackRobins, Hernán & Brumback
ΤύποςCausal inference / weighted regressionCausal inference weighting estimator
Θεμελιώδης πηγήRobins, 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 ↗
Εναλλακτικές ονομασίεςMSM for policy evaluation, policy MSM, causal MSM, structural policy weighting modelIPW, IPTW, inverse probability of treatment weighting, marginal structural model weighting
Συναφείς65
ΣύνοψηA Policy Evaluation Marginal Structural Model (MSM) is a causal inference framework that estimates the population-average effect of a policy by using inverse probability weighting to create a pseudo-population in which treatment assignment is independent of measured confounders, enabling unbiased comparison of potential outcomes under different policy scenarios 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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ScholarGateΣύγκριση μεθόδων: Policy Evaluation Marginal Structural Model · Inverse Probability Weighting. Ανακτήθηκε στις 2026-06-18 από https://scholargate.app/el/compare