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We propose a flexible joint longitudinal-survival framework to examine theassociation between longitudinally collected biomarkers and a time-to-eventendpoint. More specifically, we use our method for analyzing the survivaloutcome of end-stage renal disease patients with time-varying serum albuminmeasurements. Our proposed method is robust to common parametric assumptions inthat it avoids explicit distributional assumptions on longitudinal measures andallows for subject-specific baseline hazard in the survival component. Fullyjoint estimation is performed to account for the uncertainty in the estimatedlongitudinal biomarkers included in the survival model.

A Flexible Joint Longitudinal-Survival Model for Analysis of End-Stage Renal Disease Data