Abstract
We propose a Bayesian approach for estimating the hazard functions under the constraint of a monotone hazard ratio. We construct a model for the monotone hazard ratio utilizing the Cox’s proportional hazards model with a monotone time-dependent coefficient. To reduce computational complexity, we use a signed gamma process prior for the time-dependent coefficient and the Bayesian bootstrap prior for the baseline hazard function. We develope an efficient MCMC algorithm and illustrate the proposed method on simulated and real data sets.
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Kim, Y., Park, J.K. & Kim, G. Bayesian analysis for monotone hazard ratio. Lifetime Data Anal 17, 302–320 (2011). https://doi.org/10.1007/s10985-010-9181-x
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DOI: https://doi.org/10.1007/s10985-010-9181-x