B1132
Title: Robust joint modelling of longitudinal data and survival data: Detection and downweighting of longitudinal measurements
Authors: Freedom Gumedze - University of Cape Town (South Africa) [presenting]
Abstract: Mixed-effects location-scale models allow simultaneous modelling of between-subject and within-subject variability. These models include log-linear models for the between-subject and within-subject variability. The log-linear models could potentially include covariates. The models assume that the residual errors and the random effects are normally distributed. This makes them sensitive to outliers. These models have been extended to joint models of longitudinal data and time-to-event data. We explore Cook-type influence diagnostics for the mixed-effects location-scale model, assumed for the longitudinal sub-model, and an approach to down-weight outlying subjects. We illustrate the methods using data from a large cardiology clinical trial.
