Bayesian Analysis of Failure Time Data Using P-Splines

By Matthias Kaeding

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.

• Format: Paperback
• Language: English
• ISBN: 3658083921
• ISBN13: 9783658083922
• Release Date: January 2015
• Publisher: Springer Spektrum
• Length: 110 Pages
• Weight: 0.37 lbs.
• Dimensions: 0.3" x 5.8" x 8.3"