WITHDRAWN: Longitudinal variable selection under joint modeling of longitudinal and survival data

Music City Center 

Joint modeling of longitudinal and survival data is commonly used to study their association, and to make dynamic risk prediction of the event based on the longitudinal data. Typically, a multivariate linear mixed effect mode is used for the longitudinal submodel, and the Cox proportional hazard model is used for the survival submodel, and shared random effects are used to account for their association. Challenges arise when the number of longitudinal variables increases. We develop a longitudinal variable selection method for the joint modeling of multivariate longitudinal measurements and survival time. The longitudinal variables in the survival submodel are selected by penalized likelihood method, where a Group Lasso is imposed on the coefficients of random intercept and random slope in the survival submodel. Numerical studies are conducted to validate and illustrate the proposed procedure.