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Bejzijanovska Košova regresija×Bejzijev model mešovitih efekata×
OblastStatistikaStatistika
PorodicaRegression modelRegression model
Godina nastanka1972 (Cox PH); 2001 (Bayesian treatment)1990s–2000s (modern Bayesian MCMC era)
TvoracCox (1972) for the base model; Bayesian formulation by Sinha, Chen & Ghosh (1990s); comprehensive treatment by Ibrahim, Chen & Sinha (2001)Gelman, Hill, and the broader Bayesian hierarchical modeling tradition
TipSurvival regressionBayesian regression model
Temeljni izvorIbrahim, J. G., Chen, M.-H., & Sinha, D. (2001). Bayesian Survival Analysis. Springer. ISBN: 978-0387952772Gelman, A., & Hill, J. (2007). Data Analysis Using Regression and Multilevel/Hierarchical Models. Cambridge University Press. ISBN: 978-0521686891
Drugi naziviBayesian Cox PH model, Bayesian proportional hazards model, Bayesian survival regression, BCoxBayesian multilevel model, Bayesian random effects model, Bayesian LME, Bayesian hierarchical mixed model
Srodne65
SažetakBayesian Cox regression combines the Cox proportional hazards model for time-to-event data with Bayesian inference. Instead of point estimates, it produces full posterior distributions over the hazard ratios, naturally incorporating prior knowledge and providing coherent uncertainty quantification even with small samples or informative censoring.The Bayesian mixed effects model extends the classical mixed effects framework by placing prior distributions on all parameters — fixed effects, random effect variances, and residual variance — and updating them with data to produce full posterior distributions. This provides coherent uncertainty quantification for both population-level and group-level effects simultaneously.
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ScholarGateUporedite metode: Bayesian Cox Regression · Bayesian Mixed Effects Model. Preuzeto 2026-06-15 sa https://scholargate.app/sr/compare