Destructive weighted Poisson cure rate models with bivariate random effects: Classical and Bayesian approaches

Abstract

In this paper, random effects are included in the destructive weighted Poisson cure rate model. For parameter estimation we implemented a classical approach based on the restricted maximum likelihood (REML) methodology and a Bayesian approach based on Dirichlet process priors. A small scale simulation study is conducted to discuss parameter recovery and the performance of the proposed methodology is illustrated with a real data example.