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Updated: May 20, 2026

Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills
Published on: September 17, 2019
Associations between variability of risk factors and health outcomes in longitudinal studies
Michael R Elliott1, Mary D Sammel, Jessica Faul
1Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, USA. mrelliot@umich.edu
Abstract:
Many statistical methods have been developed that treat within-subject correlation that accompanies the clustering of subjects in longitudinal data settings as a nuisance parameter, with the focus of analytic interest being on mean outcome or profiles over time. However, there is evidence that in certain settings, underlying variability in subject measures may also be important in predicting future health outcomes of interest. Here, we develop a method for combining information from mean profiles and residual variance to assess associations with categorical outcomes in a joint modeling framework. We consider an application to relating word recall measures obtained over time to dementia onset from the Health and Retirement Survey.
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