A Flexible Joint Longitudinal-Survival Model for Analyzing Longitudinally Sampled Biomarkers

We propose a flexible joint longitudinal-survival framework to examine the association between longitudinally collected biomarkers and time-to-event endpoint. More specifically, we use our method for analyzing survival outcome of end-stage renal disease patients with time-varying serum albumin measurements. Our proposed method is robust to common parametric assumptions in that it avoids explicit specification the distribution longitudinal responses allows for subject-specific baseline hazard component. Fully estimation performed to account uncertainty estimated biomarkers are included model.