Bayesian hierarchical model for multiple repeated measures and survival data: an application to Parkinson's disease.

ABSTRACT: Multilevel item response theory models have been increasingly used to analyze the multivariate longitudinal data of mixed types (e.g., continuous and categorical) in clinical studies. To address the possible correlation between multivariate longitudinal measures and time to terminal events (e.g., death and dropout), joint models that consist of a multilevel item response theory submodel and a survival submodel have been previously developed. However, in multisite studies, multiple patients are recruited and treated by the same clinical site. There can be a significant site correlation because of common environmental and socioeconomic status, and similar quality of care within site. In this article, we develop and study several hierarchical joint models with the hazard of terminal events de

SUBMITTER: Luo S 

PROVIDER: S-EPMC4184935 | biostudies-literature | 2014 Oct

REPOSITORIES: biostudies-literature