Shared parameter modeling of longitudinal data allowing for possibly informative visiting process and terminal event.

ABSTRACT: Joint modeling of longitudinal and time-to-event data, particularly through shared parameter models (SPMs), is a common approach for handling longitudinal marker data with an informative terminal event. A critical but often neglected assumption in this context is that the visiting/observation process is noninformative, depending solely on past marker values and visit times. When this assumption fails, the visiting process becomes informative, resulting potentially to biased SPM estimates. Existing methods generally rely on a conditional independence assumption, positing that the marker model, visiting process, and time-to-event model are independent given shared or correlated random effects. Moreover, they are typically built on an intensity-based visiting process using calendar time. This

SUBMITTER: Thomadakis C 

PROVIDER: S-EPMC11911807 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature