方法对比
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| 贝叶斯生存分析× | Cox比例风险回归× | Kaplan-Meier生存估计量× | |
|---|---|---|---|
| 领域≠ | 贝叶斯 | 生存分析 | 生存分析 |
| 方法族≠ | Bayesian methods | Survival analysis | Survival analysis |
| 起源年份≠ | 2001 | 1972 | 1958 |
| 提出者≠ | Ibrahim, Chen & Sinha | Cox, D. R. | Kaplan, E. L. & Meier, P. |
| 类型≠ | Bayesian time-to-event model | Semi-parametric hazard regression model | Non-parametric survival estimator |
| 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 ↗ | Kaplan, E. L. & Meier, P. (1958). Nonparametric Estimation from Incomplete Observations. Journal of the American Statistical Association, 53(282), 457–481. DOI ↗ |
| 别名≠ | bayesian sağkalım analizi, bayesian time-to-event analysis, bayesian hazard model | cox ph model, proportional hazards model, cox ph regression, Cox Orantılı Tehlikeler Regresyonu | product-limit estimator, km curve, kaplan-meier sağkalım analizi |
| 相关≠ | 4 | 3 | 2 |
| 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. | The Kaplan-Meier estimator, introduced by Kaplan and Meier in 1958, is a non-parametric method that estimates the survival curve — the probability of remaining event-free over time — from right-censored time-to-event data. The log-rank test is the companion procedure used to compare survival curves between groups. |
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