Abstract:
The family of power series cure rate models provides a flexible modelling framework for survival data of populations with a cure fraction. In this work we present a simplified estimation procedure for the maximum likelihood (ML) approach. ML estimates are obtained via the Expectation-Maximization (EM) algorithm where the expectation step involves computation of the expected number of concurrent causes for each individual. It has the big advantage that the maximization step can be decomposed into separate maximizations of two lower dimensional functions of the regression and survival distribution parameters, respectively. Two simulation studies are performed: the first to investigate the accuracy of the estimation procedure for different numbers of covariates and the second to compare our proposal with the direct maximization of the observed log-likelihood function. Finally, we illustrate the technique for parameter estimation on a data set of survival times for patients with malignant melanoma. Keywords: EM algorithm, Power series distribution, Promotion time cure rate model, Survival analysis.
