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Bayesiansk överlevnadsanalys×Cox proportionella riskmodellen×
ÄmnesområdeBayesiansk statistikÖverlevnadsanalys
FamiljBayesian methodsSurvival analysis
Ursprungsår20011972
UpphovspersonIbrahim, Chen & SinhaCox, D. R.
TypBayesian time-to-event modelSemi-parametric hazard regression model
UrsprungskällaIbrahim, 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
Närliggande43
SammanfattningBayesian 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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ScholarGateJämför metoder: Bayesian Survival Analysis · Cox Regression. Hämtad 2026-06-17 från https://scholargate.app/sv/compare