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Bayesiaanse Overlevingsanalyse×Cox Proportionele Risico's Regressie×
VakgebiedBayesiaanse statistiekOverlevingsanalyse
FamilieBayesian methodsSurvival analysis
Jaar van ontstaan20011972
GrondleggerIbrahim, Chen & SinhaCox, D. R.
TypeBayesian time-to-event modelSemi-parametric hazard regression model
Oorspronkelijke bronIbrahim, 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 ↗
Aliassenbayesian sağkalım analizi, bayesian time-to-event analysis, bayesian hazard modelcox ph model, proportional hazards model, cox ph regression, Cox Orantılı Tehlikeler Regresyonu
Verwant43
SamenvattingBayesian 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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ScholarGateMethoden vergelijken: Bayesian Survival Analysis · Cox Regression. Geraadpleegd op 2026-06-17 via https://scholargate.app/nl/compare