Applied Statistics and Data Science Seminar on Monday, October 9, 2023

Title: Joint copula-frailty approach to model clustered survival data with dependent censoring (PhD proposal)

Venue and time: ISRT, 2:00 pm

Presenter:  Nasrin Sultana, PhD student at ISRT

Abstract:

With the development of modern medical technology, in many situations naturally a fraction of patients can be cured, or the disease free, while the non-cured patients lengthen their survival time. Recurrence of a disease or event is a very common phenomenon in biomedical studies. The uncured patients experience the recurrence of the disease because of some unobserved random effects or heterogeneity. Dependent censoring may arise in some situations when the right censoring is completely or partly caused by an event other than the terminal event of interest, possibly due to these random effects. We aim at developing both a joint frailty model and a joint frailty copula model for such recurrent event lifetime data considering cure fraction that captures the heterogeneity due to dependent censoring. To achieve dependent censoring, we also need to add joint modelling of recurrent time and time to death where time to death determines the censoring mechanism. A likelihood-based technique has been developed for the proposed models. The Expectation-Maximization (EM) and Monte Carlo Expectation-Maximization (MCEM) algorithms are being developed to carry out the underlying parameter estimation and inference procedures.