Title: A variable selection method for the joint modelling of longitudinal and survival data with its application
Authors: Tao Wang - Yunnan Normal University (China) [presenting]
Abstract: Although there has been extensive research for joint modelling method of longitudinal and survival data in the last two decades motivated by the requirements of increasingly application and the importance of such joint models has been increasingly recognized, but the research on variable selection method for joint models of longitudinal and survival outcomes with lower computational load is still getting on slowly. We propose a novel Bayesian SCAD variable selection method for semi-parametric joint model which consists of a semi-parametric mixed effects model for longitudinal data and a semi-parametric Cox proportional hazards model for survival data linked through shared random effects. We develop the computational program for such a variable selection method. Simulation studies and real data analysis demonstrate that our method performs well.