Bayesian estimation of the Cox model under different hazard rate shape assumptions via slice sampling

Thomas Kirschenmann, Paul Damien and Stephen Walker

Journal of Applied Statistics, 2018, vol. 45, issue 12, 2295-2306

Abstract: In this paper, we provide a full Bayesian analysis for Cox's proportional hazards model under different hazard rate shape assumptions. To this end, we select the modified Weibull distribution family to model failure rates. A novel Markov chain Monte Carlo method allows one to tackle both exact and right-censored failure time data. Both simulated and real data are used to illustrate the methods.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:taf:japsta:v:45:y:2018:i:12:p:2295-2306

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DOI: 10.1080/02664763.2017.1420147

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