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Análisis de Supervivencia Bayesiano×Estimador de Supervivencia de Kaplan-Meier×
CampoBayesianoSupervivencia
FamiliaBayesian methodsSurvival analysis
Año de origen20011958
Autor originalIbrahim, Chen & SinhaKaplan, E. L. & Meier, P.
TipoBayesian time-to-event modelNon-parametric survival estimator
Fuente seminalIbrahim, J.G., Chen, M.-H. & Sinha, D. (2001). Bayesian Survival Analysis. Springer. DOI ↗Kaplan, E. L. & Meier, P. (1958). Nonparametric Estimation from Incomplete Observations. Journal of the American Statistical Association, 53(282), 457–481. DOI ↗
Aliasbayesian sağkalım analizi, bayesian time-to-event analysis, bayesian hazard modelproduct-limit estimator, km curve, kaplan-meier sağkalım analizi
Relacionados42
ResumenBayesian survival analysis applies Bayesian inference to time-to-event models — Cox proportional hazards, parametric (Weibull, exponential), and cure models. Formalised comprehensively by Ibrahim, Chen and Sinha (2001), the approach encodes prior knowledge about hazard rates and regression coefficients, then updates it with censored survival data to yield posterior hazard ratios and credible intervals rather than single point estimates.The Kaplan-Meier estimator, introduced by Kaplan and Meier in 1958, is a non-parametric method that estimates the survival curve — the probability of remaining event-free over time — from right-censored time-to-event data. The log-rank test is the companion procedure used to compare survival curves between groups.
ScholarGateConjunto de datos
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ScholarGateComparar métodos: Bayesian Survival Analysis · Kaplan-Meier. Recuperado el 2026-06-17 de https://scholargate.app/es/compare