A New lifetime model for multivariate survival data with a surviving fraction
Cancho, Vicente G.
Dey, Dipak K.
Barriga, Gladys D. C. [UNESP]
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Taylor & Francis Ltd
In this paper we propose a new lifetime model for multivariate survival data with a surviving fraction. We develop this model assuming that there are m types of unobservable competing risks, where each risk is related to a time of the occurrence of an event of interest. We explore the use of Markov chain Monte Carlo methods to develop a Bayesian analysis for the proposed model. We also perform a simulation study in order to analyse the frequentist coverage probabilities of credible interval derived from posteriors. Our modelling is illustrated through a real data set.
Bayesian inference, competing risks, MCMC, multivariate survival models, cure rate models, cured fraction
Journal Of Statistical Computation And Simulation. Abingdon: Taylor & Francis Ltd, v. 86, n. 2, p. 279-292, 2016.