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Análisis de Supervivencia Bayesiano×Regresión de Riesgos Proporcionales de Cox×
CampoBayesianoSupervivencia
FamiliaBayesian methodsSurvival analysis
Año de origen20011972
Autor originalIbrahim, Chen & SinhaCox, D. R.
TipoBayesian time-to-event modelSemi-parametric hazard regression model
Fuente seminalIbrahim, J.G., Chen, M.-H. & Sinha, D. (2001). Bayesian Survival Analysis. Springer. DOI ↗Cox, D. R. (1972). Regression Models and Life-Tables. Journal of the Royal Statistical Society: Series B, 34(2), 187–202. DOI ↗
Aliasbayesian sağkalım analizi, bayesian time-to-event analysis, bayesian hazard modelcox ph model, proportional hazards model, cox ph regression, Cox Orantılı Tehlikeler Regresyonu
Relacionados43
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.Cox proportional hazards regression, introduced by D. R. Cox in 1972, is a semi-parametric model that estimates how one or more covariates affect the hazard — the instantaneous rate of experiencing an event — while leaving the baseline hazard function unspecified. It is the standard multivariable method in survival analysis and produces hazard ratios that quantify the relative risk associated with each predictor.
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ScholarGateComparar métodos: Bayesian Survival Analysis · Cox Regression. Recuperado el 2026-06-17 de https://scholargate.app/es/compare