For a heart transplant patient, the risk of graft rejection and risk of death are likely to be associated. Two fully specified Bayesian models for recurrent events with dependent termination are applied to investigate the potential relationships between these two types of risk as well as association with risk factors. We particularly focus on the choice of priors, selection of the appropriate prediction model, and prediction methods for these two types of risk for an individual patient. Our prediction tools can be easily implemented and helpful to physicians for setting heart transplant patients' biopsy schedule. Copyright © 2012 John Wiley & Sons, Ltd.
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