Bayesian Analysis of Failure Time Data Using P-Splines (BestMasters)

Bayesian Analysis of Failure Time Data Using P-Splines (BestMasters)

ISBN: 9783658083922
Publisher: Springer Spektrum
Edition: 2015
Publication Date: 2014-12-27
Number of pages: 110
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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.

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