A Novel Bayesian Continuous Piecewise Linear Log‐Hazard Model, With Estimation and Inference via Reversible Jump...
Dr. Andrew Chapple
Assistant Professor
Biostatistics Program
LSU Health Sciences Center School of Public Health
A Novel Bayesian Continuous Piecewise Linear Log‐Hazard Model, With Estimation and Inference via Reversible Jump Markov Chain Monte Carlo
We present a reversible jump Bayesian piecewise log‐linear hazard model that extends the Bayesian piecewise exponential hazard to a continuous function of piecewise linear log hazards. A simulation study encompassing several different hazard shapes, accrual rates, censoring proportion, and sample sizes showed that the Bayesian piecewise linear log‐hazard model estimated the true mean survival time and survival distributions better than the piecewise exponential hazard. Survival data from Wake Forest Baptist Medical Center is analyzed by both methods and the posterior results are compared.
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- Sponsor(s)
- Medicine: Biostatistics
- Speaker(s)
- Dr. Andrew Chapple
- Audience
- School of Medicine, VCU Faculty, VCU Staff, VCU Students