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Kaplan-Meierova analiza prilagođena riziku×Uteživanje inverznom vjerojatnošću tretmana (IPW / IPTW)×
PodručjeEpidemiologijaUzročno zaključivanje
ObiteljProcess / pipelineRegression model
Godina nastanka2001–2004 (formal statistical framework for weighted KM curves)2000
TvoracConceptual basis: Kaplan & Meier (1958); risk-adjustment via IPTW formalised by Hernán, Brumback & Robins (2001), with practical implementation by Cole & Hernán (2004)Robins, Hernán & Brumback
VrstaAdjusted non-parametric survival methodCausal inference weighting estimator
Temeljni izvorCole, S. R., & Hernan, M. A. (2004). Adjusted survival curves with inverse probability weights. Computer Methods and Programs in Biomedicine, 75(1), 45–49. 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 naziviweighted Kaplan-Meier, IPTW-adjusted Kaplan-Meier, propensity-score-weighted survival curves, adjusted survival curvesIPW, IPTW, inverse probability of treatment weighting, marginal structural model weighting
Srodne55
SažetakRisk-adjusted Kaplan-Meier analysis combines the non-parametric Kaplan-Meier estimator with inverse probability of treatment weighting (IPTW) or similar risk-adjustment procedures to produce survival curves that are comparable across groups as if the groups had identical distributions of baseline confounders. It is the observational-study analogue of plotting survival curves from a randomised trial.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: Risk-adjusted Kaplan-Meier analysis · Inverse Probability Weighting. Preuzeto 2026-06-18 s https://scholargate.app/hr/compare