Bayesian analysis of discrete survival data with a hidden Markov chain.
This paper considers the discrete survival data from a Bayesian point of view. A sequence of the baseline hazard functions, which plays an important role in the discrete hazard function, is modeled with a hidden Markov chain. It is explained how the resultant model is implemented via Markov chain Monte Carlo methods. The model is illustrated by an application of real data.
Kozumi
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Faculty of Economics, Hokkaido University, Kita 9 Nishi 7, Kita-ku, Sapporo 060-0809, Japan. kozumi@econ.hokudai.ac.jp
D001499:Bayes Theorem; D001699:Biometry / Q000379:methods*; D003131:Combined Modality Therapy; D006258:Head and Neck Neoplasms / Q000188:drug therapy / Q000401:mortality / Q000532:radiotherapy; D006801:Humans; D008390:Markov Chains; D009010:Monte Carlo Method; D011336:Probability; D016019:Survival Analysis