Marginal regression analysis of clustered failure time data with a cure fraction

Abstract

We consider a marginal mixture cure model for clustered survival data in which there may be a cure fraction and the survival times may be correlated. We propose a generalized estimating equation approach by incorporating working correlation matrices into an EM algorithm to estimate the regression coefficients and the baseline hazard function in the marginal model. The estimators of the regression parameters and the baseline hazard function are shown to be consistent and asymptotically normal, and their variances can be consistently estimated by a sandwich estimator. The proposed method is simple to use, and our simulation study shows the proposed method is more efficient than the existing marginal methods that ignore the correlation within clusters. An application of the proposed method to data from a smoking cessation study is demonstrated.