  We are interested in survival analysis of hemodialysis patients for whom
several biomarkers are recorded over time. Motivated by this challenging
problem, we propose a general framework for multivariate joint
longitudinal-survival modeling that can be used to examine the association
between several longitudinally recorded covariates and a time-to-event
endpoint. Our method allows for simultaneous modeling of longitudinal
covariates by taking their correlation into account. This leads to a more
efficient method for modeling their trajectories over time, and hence, it can
better capture their relationship to the survival outcomes.
