Bayesian analysis of generalized odds-rate hazards models for survival data. (English) Zbl 1162.62430
Summary: In the analysis of censored survival data the Cox proportional hazards model is extremely popular among the practitioners. However, in many real-life situations the proportionality of the hazard ratios does not seem to be an appropriate assumption. To overcome such a problem, we consider a class of nonproportional hazards models known as generalized odds-rate class of regression models. The class is general enough to include several commonly used models, such as proportional hazards model, proportional odds model, and the accelerated life time model. The theoretical and computational properties of these models have been re-examined. The propriety of the posterior has been established under some mild conditions. A simulation study is conducted and a detailed analysis of the data from a prostate cancer study is presented to further illustrate the proposed methodology.
MSC:
| 62P10 | Applications of statistics to biology and medical sciences; meta analysis |
| 62F15 | Bayesian inference |
| 62N02 | Estimation in survival analysis and censored data |
Keywords:
Cox model; Gibbs sampling; Piecewise exponential model; Proportional hazards model; Proportional odds model; Posterior distributionReferences:
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