The generalized exponential cure rate model with covariates

Abstract

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.cure rate, long-term survivor, generalized exponential distribution, EM algorithm, goodness-of-fit,

Absolute continuous bivariate generalized exponential distribution

“…1. This plot can be used as a goodness of fit for the GE distribution, see Kannan et al (2010) It is clear from all this that the GE distribution can be used to fit the marginals reasonably well. .…”

Tests for cured proportion for recurrent event count data – Uncensored case with covariates

“…It was observed that the increase in the duration was mainly for the estimation of the parameters because the number of iterations required for the convergence of the Newton-Raphson method was considerably more. W of the score test is conservative for n =20 and 40, whereas the variant 13 W is liberal for the same. Both these tests maintain type I error rate at n =80.…”

Cure Rate Models Considering The Burr XII Distribution in Presence of Covariate

“…Yamaguchi (1992) considered the generalized log-gamma distribution for the mixture cure rate model in the context of accelerated failure-time regression models. The Gompertz distribution was considered by Gieser et al (1998), while the exponentiated Weibull and exponentiated exponential distributions were considered, respectively, by Bolfarine and Cancho (2001) and Kannan et al (2010). The Conway-Maxwell Poisson cure rate model was proposed by Rodrigues et al (2009a) as an alternative to the cure rate model discussed by Yin and Ibrahim (2005).…”