Evaluating the association between latent classes and competing risks outcomes with multiphenotype data.

ABSTRACT: Latent class analysis is an intuitive tool to characterize disease phenotype heterogeneity. With data more frequently collected on multiple phenotypes in chronic disease studies, it is of rising interest to investigate how the latent classes embedded in one phenotype are related to another phenotype. Motivated by a cohort with mild cognitive impairment (MCI) from the Uniform Data Set (UDS), we propose and study a time-dependent structural model to evaluate the association between latent classes and competing risk outcomes that are subject to missing failure types. We develop a two-step estimation procedure which circumvents latent class membership assignment and is rigorously justified in terms of accounting for the uncertainty in classifying latent classes. The new method also properly ad

SUBMITTER: Fei T 

PROVIDER: S-EPMC8926941 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature