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Long-term survival models with latent activation under a flexible family of distributions

2013; UNIVERSIDADE DE SÃO PAULO; Volume: 27; Issue: 4 Linguagem: Inglês

10.1214/12-bjps186

2317-6199

Vicente G. Cancho, Mário de Castro, Dipak K. Dey,

Statistical Methods and Bayesian Inference

In this paper, we propose a new cure rate survival model under a flexible family of distributions. Our approach enables different underlying activation mechanisms that lead to the event of interest. The number of competing causes of the event of interest follows a power series distribution. This model includes the standard mixture cure model and the promotion time cure model. The model is parametrized in terms of the cured fraction, which is then linked to covariates. We carried out a simulation study to assess some properties of our proposal. An illustrative example with a real data set is provided to illustrate the models.