เปรียบเทียบวิธี

	การถดถอยการรอดชีพแบบเบย์ (Bayesian Survival Regression)	การถดถอยแบบรอดชีพ
สาขาวิชา	สถิติศาสตร์	สถิติศาสตร์
ตระกูล	Regression model	Regression model
ปีกำเนิด	1990s–2001	1980s
ผู้ริเริ่ม	Ibrahim, Chen & Sinha (seminal textbook treatment, 2001); broader Bayesian framework: Gelman et al.	Kalbfleisch & Prentice; Cox & Oakes
ประเภท	Bayesian parametric/semiparametric regression	Parametric survival model
แหล่งต้นตำรับ	Ibrahim, J. G., Chen, M.-H., & Sinha, D. (2001). Bayesian Survival Analysis. Springer. ISBN: 978-0387952772	Kalbfleisch, J. D., & Prentice, R. L. (2002). The Statistical Analysis of Failure Time Data (2nd ed.). Wiley. ISBN: 978-0471363576
ชื่อเรียกอื่น	Bayesian time-to-event regression, Bayesian parametric survival model, Bayesian survival analysis, Bayesian accelerated failure time model	accelerated failure time model, AFT model, parametric survival model, time-to-event regression
ที่เกี่ยวข้อง	5	3
สรุป	Bayesian Survival Regression combines parametric or semiparametric survival models — such as Weibull, log-normal, or Cox proportional hazards — with Bayesian inference. Instead of point estimates, it produces full posterior distributions for regression coefficients and the baseline hazard, naturally handling censored observations and incorporating prior knowledge about event times or covariate effects.	Survival regression models the time until an event occurs — such as death, failure, or relapse — as a function of covariates. Unlike ordinary regression, it properly accounts for censored observations (cases where the event had not yet occurred at the end of follow-up) by specifying a parametric distribution for the survival time and estimating covariate effects via maximum likelihood.