García-Donato, GonzaloCabras, StefanoCastellanos, María Eugenia2023-09-272023-09-272023García-Donato, G., Cabras, S. & Castellanos, M.E. (2023) Model uncertainty quantification in Cox regression. Biometrics, 79, 1726–1736. https://doi.org/10.1111/biom.138231541-0420https://hdl.handle.net/10115/24583Ministerio de Ciencia e Innovación. Grant Number: Grant PID2019-104790GB-I00 funded by MCIN/AEIWeconsidercovariateselectionandtheensuingmodeluncertaintyaspectsinthecontextofCoxregression.Theperspectivewetakeisprobabilistic,andwehandleit within a Bayesian framework. One of the critical elements in variable/modelselection is choosing a suitable prior for model parameters. Here, we derive theso-called conventional prior approach and propose a comprehensive implemen-tation that results in an automatic procedure. Our simulation studies and realapplications show improvements over existing literature. For the sake of repro-ducibility but also for its intrinsic interest for practitioners, a web applicationrequiring minimum statistical knowledge implements the proposed approach.engAtribución-NoComercial 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc/4.0/Bayesian variable selectionconventional priorFisher informationmedian modelsurvival analysisinfo:eu-repo/semantics/article10.1111/biom.13823info:eu-repo/semantics/openAccess