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Anàlisi bayesiana de la supervivència×Regressió de Cox amb perills proporcionals×
CampBayesiàSupervivència
FamíliaBayesian methodsSurvival analysis
Any d'origen20011972
Autor originalIbrahim, Chen & SinhaCox, D. R.
TipusBayesian time-to-event modelSemi-parametric hazard regression model
Font 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 ↗
Àliesbayesian sağkalım analizi, bayesian time-to-event analysis, bayesian hazard modelcox ph model, proportional hazards model, cox ph regression, Cox Orantılı Tehlikeler Regresyonu
Relacionats43
ResumBayesian 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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ScholarGateCompara mètodes: Bayesian Survival Analysis · Cox Regression. Recuperat el 2026-06-17 de https://scholargate.app/ca/compare