Bayesian Analysis of Failure Time Data Using P-Splines E-Book

Matthias Kaeding

• Herausgeber: Springer Fachmedien Wiesbaden GmbH
• Kategorie: Wissenschaft und neue Technologien
• Serie: BestMasters
• Sprache: Englisch

Veröffentlichungsjahr: 2014

Beschreibung

Matthias Kaeding discusses Bayesian methods for analyzing discrete and continuous failure times where the effect of time and/or covariates is modeled via P-splines and additional basic function expansions, allowing the replacement of linear effects by more general functions. The MCMC methodology for these models is presented in a unified framework and applied on data sets. Among others, existing algorithms for the grouped Cox and the piecewise exponential model under interval censoring are combined with a data augmentation step for the applications. The author shows that the resulting Gibbs sampler works well for the grouped Cox and is merely adequate for the piecewise exponential model.