The generalized exponential cure rate model with covariates

In this article, we consider a parametric survival model that is appropriate when the population of interest contains long-term survivors or immunes. The model referred to as the cure rate model was introduced by Boag [1] in terms of a mixture model that included a component representing the proportion of immunes and a distribution representing the life times of the susceptible population.We propose a cure rate model based on the generalized exponential distribution that incorporates the effects of risk factors or covariates on the probability of an individual being a long-time survivor. Maximum likelihood estimators of the model parameters are obtained using the the expectation-maximisation (EM) algorithm. A graphical method is also provided for assessing the goodness-of-fit of the model.We present an example to illustrate the fit of this model to data that examines the effects of different risk factors on relapse time for drug addicts