পদ্ধতির তুলনা করুন

	বেয়েশীয় উত্তরজীবী বিশ্লেষণ	Cox Proportional Hazards Regression
ক্ষেত্র	বেইসীয়	উত্তরজীবিতা
পরিবার	Bayesian methods	Survival analysis
উদ্ভবের বছর	2001	1972
প্রবর্তক	Ibrahim, Chen & Sinha	Cox, D. R.
ধরন	Bayesian time-to-event model	Semi-parametric hazard regression model
মৌলিক উৎস	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.
অপর নাম	bayesian sağkalım analizi, bayesian time-to-event analysis, bayesian hazard model	cox ph model, proportional hazards model, cox ph regression, Cox Orantılı Tehlikeler Regresyonu
সম্পর্কিত	4	3
সারসংক্ষেপ	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.