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A novel Bayesian continuous piecewise linear log-hazard model, with estimation and inference via reversible jump
Andrew G Chapple1, Taylor Peak2, Ashok Hemal2
1Biostatistics Program, Louisiana State University Health Sciences Center, School of Public Health, New Orleans, Louisiana.
Abstract:
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 piecewsie 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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