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Bayesovská regresní analýza přežití×Proporcionální regresní model rizik Coxe×
OborStatistikaAnalýza přežití
RodinaRegression modelSurvival analysis
Rok vzniku1990s–20011972
TvůrceIbrahim, Chen & Sinha (seminal textbook treatment, 2001); broader Bayesian framework: Gelman et al.Cox, D. R.
TypBayesian parametric/semiparametric regressionSemi-parametric hazard regression model
Původní zdrojIbrahim, J. G., Chen, M.-H., & Sinha, D. (2001). Bayesian Survival Analysis. Springer. ISBN: 978-0387952772Cox, D. R. (1972). Regression Models and Life-Tables. Journal of the Royal Statistical Society: Series B, 34(2), 187–202. DOI ↗
Další názvyBayesian time-to-event regression, Bayesian parametric survival model, Bayesian survival analysis, Bayesian accelerated failure time modelcox ph model, proportional hazards model, cox ph regression, Cox Orantılı Tehlikeler Regresyonu
Příbuzné53
ShrnutíBayesian 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.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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ScholarGatePorovnat metody: Bayesian Survival regression · Cox Regression. Získáno 2026-06-17 z https://scholargate.app/cs/compare