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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Bayesian Analysis of Failure Time Data Using P-Splines

Bayesian Analysis of Failure Time Data Using P-Splines

Kaeding, Matthias

Paperback

Series: Bestmasters

Medical ReferenceAnatomy & PhysiologyProbability & Statistics

ISBN10: 3658083921
ISBN13: 9783658083922
Publisher: Springer Nature
Published: Jan 12 2015
Pages: 110
Weight: 0.37
Height: 0.29 Width: 5.83 Depth: 8.27
Language: English
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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