Dr. Lang Wu
Department of Statistics
University of British Columbia
Title: "Joint Inference for Nonlinear Mixed-Effects Models and Time-to-Event Models with Missing Data"
Nonlinear mixed-effects (NLME) models are widely used in many longitudinal studies such as HIV
viral dynamics. In some studies, we may need to simultaneously consider a longitudinal process
and a time-to-event process, so joint statistical inference is often required. In addition, there
may be measurement errors and missing data in the variables. In this talk we consider a NLME model
for the longitudinal process and a survival model with random effects for the time-to-event process,
incorporating measurement errors and missing data. Our methods are illustrated using an AIDS dataset.