مقایسهٔ روش‌ها

	تحلیل بقای بیزی	رگرسیون کوکس (Cox Proportional Hazards Regression)
حوزه	بیزی	تحلیل بقا
خانواده	Bayesian methods	Survival analysis
سال پیدایش	2001	1972
پدیدآور	Ibrahim, Chen & Sinha	Cox, D. R.
نوع	Bayesian time-to-event model	Semi-parametric hazard regression model
منبع بنیادین	Ibrahim, J.G., Chen, M.-H. & Sinha, D. (2001). Bayesian Survival Analysis. Springer.	Cox, D. R. (1972). Regression Models and Life-Tables. Journal of the Royal Statistical Society: Series B, 34(2), 187–202.
نام‌های دیگر	bayesian sağkalım analizi, bayesian time-to-event analysis, bayesian hazard model	cox ph model, proportional hazards model, cox ph regression, Cox Orantılı Tehlikeler Regresyonu
مرتبط	4	3
خلاصه	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.