Joint modelling of longitudinal and survival data: incorporating delayed entry and an assessment of model misspecification.

ABSTRACT: A now common goal in medical research is to investigate the inter-relationships between a repeatedly measured biomarker, measured with error, and the time to an event of interest. This form of question can be tackled with a joint longitudinal-survival model, with the most common approach combining a longitudinal mixed effects model with a proportional hazards survival model, where the models are linked through shared random effects. In this article, we look at incorporating delayed entry (left truncation), which has received relatively little attention. The extension to delayed entry requires a second set of numerical integration, beyond that required in a standard joint model. We therefore implement two sets of fully adaptive Gauss-Hermite quadrature with nested Gauss-Kronrod quadrature (

SUBMITTER: Crowther MJ 

PROVIDER: S-EPMC5019272 | biostudies-literature | 2016 Mar

REPOSITORIES: biostudies-literature