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Ważenie odwrotnością prawdopodobieństwa leczenia (IPW / IPTW)×Analiza przyczynowego pośrednictwa (naturalny efekt bezpośredni i pośredni)×
DziedzinaWnioskowanie przyczynoweWnioskowanie przyczynowe
RodzinaRegression modelRegression model
Rok powstania20002010
TwórcaRobins, Hernán & BrumbackPearl (2001); general framework by Imai, Keele & Tingley (2010)
TypCausal inference weighting estimatorCounterfactual causal decomposition
Źródło pierwotneRobins, J. M., Hernán, M. A., & Brumback, B. (2000). Marginal Structural Models and Causal Inference in Epidemiology. Epidemiology, 11(5), 550-560. DOI ↗Pearl, J. (2001). Direct and Indirect Effects. In Proceedings of the Seventeenth Conference on Uncertainty in Artificial Intelligence (UAI), 411-420. link ↗
Inne nazwyIPW, IPTW, inverse probability of treatment weighting, marginal structural model weightingnatural direct effect, natural indirect effect, NDE / NIE decomposition, counterfactual mediation
Pokrewne55
PodsumowanieInverse 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.Causal mediation analysis is a counterfactual framework that splits a treatment's total effect into a Natural Direct Effect (NDE) and a Natural Indirect Effect (NIE) that runs through a mediator. The modern general approach was formalised by Pearl (2001) and Imai, Keele and Tingley (2010), giving the decomposition a precise causal interpretation.
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  3. PUBLISHED

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ScholarGatePorównaj metody: Inverse Probability Weighting · Causal Mediation Analysis. Pobrano 2026-06-18 z https://scholargate.app/pl/compare