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贝叶斯生存分析×Cox比例风险回归×
领域贝叶斯生存分析
方法族Bayesian methodsSurvival analysis
起源年份20011972
提出者Ibrahim, Chen & SinhaCox, D. R.
类型Bayesian time-to-event modelSemi-parametric hazard regression model
开创性文献Ibrahim, 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 ↗
别名bayesian sağkalım analizi, bayesian time-to-event analysis, bayesian hazard modelcox ph model, proportional hazards model, cox ph regression, Cox Orantılı Tehlikeler Regresyonu
相关43
摘要Bayesian 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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ScholarGate方法对比: Bayesian Survival Analysis · Cox Regression. 于 2026-06-17 检索自 https://scholargate.app/zh/compare