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Non-mixture cure correlated frailty models in Bayesian approach

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In this article, we develop a Bayesian approach for the estimation of two cure correlated frailty models that have been extended to the cure frailty models introduced by Yin [34]. We used the two different type of frailty with bivariate log-normal distribution instead of gamma distribution. A likelihood function was constructed based on a piecewise exponential distribution function. The model parameters were estimated by the Markov chain Monte Carlo method. The comparison of models is based on the Cox correlated frailty model with log-normal distribution. A real data set of bilateral corneal graft rejection was used to compare these models. The results of this data, based on deviance information criteria, showed the advantage of the proposed models.
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Keywords: Bayesian approach; bivariate log-normal; correlated frailty; non-mixture cure model; piecewise exponential

Document Type: Research Article

Affiliations: 1: Department of Biostatistics, School of Medical Sciences,Tarbiat Modares University, Tehran, Iran 2: Department of Statistics,Allameh Tabatabai University, Tehran, Iran

Publication date: August 1, 2011

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