02: A Trivariate Joint Modeling of Longitudinal, Recurrent and Terminal Events via Item Response Theory

Thomas M. Menino Convention & Exhibition Center 

We introduce a trivariate joint modeling framework that unifies longitudinal biomarkers, recurrent events, and terminal event risk through a latent disease‐severity process and a shared frailty component. The proposed model accommodates longitudinal outcome via an IRT formulation and captures complex relationships between disease progression and event processes. In this structure, a shared latent trait links a longitudinal outcome with both recurrent and terminal events, while a shared frailty term captures dependence between recurrent and terminal event risks. Together, these components allow the model to jointly characterize associations across longitudinal, recurrent, and terminal processes within a cohesive framework. Simulation studies show accurate parameter recovery and strong predictive performance under realistic study conditions, including sparse or irregular follow‐up. We demonstrate the utility of the approach using a cardiovascular disease dataset.

Joint Modeling

Bayesian Analysis

Item Response Theory 

Biometrics Section