Cross-sectional and Longitudinal Approaches in a Survival Mixture Model

In this article, we explore the performance of estimators in mixture survival model using simulated data recorded cross-sectionally and longitudinally. We use the maximum likelihood estimation approach in estimating the unknown model parameters. We found, in particular, that the maximum likelihood estimator for the proportion of long term survivors in longitudinal setting gain better efficiency and precision for a certain distance of recording time.