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Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills

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Recent Changes Leading to Subsequent Changes: Extensions of Multivariate Latent Difference Score Models.

Kevin J Grimm¹, Yang An, John J McArdle

¹Department of Psychology, University of California, Davis One Shields Avenue, Davis, CA 95616, kjgrimm@ucdavis.edu , 530-754-9434.

Structural Equation Modeling : a Multidisciplinary Journal

|May 3, 2013

Summary

Recent increases in lateral ventricle size predict future memory decline in older adults. This study extends latent difference score models to analyze longitudinal aging data.

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Area of Science:

Neuroscience
Psychology
Biostatistics

Background:

Latent difference score models are statistical tools used to analyze longitudinal data.
Previous models primarily focused on levels rather than changes over time.
Understanding predictors of cognitive decline is crucial for aging research.

Purpose of the Study:

To extend latent difference score models to incorporate the influence of prior changes on subsequent changes.
To investigate the relationship between changes in lateral ventricle size and memory performance over time.
To identify recent changes as predictors of future changes in cognitive function.

Main Methods:

Application of extended latent difference score models to bivariate longitudinal data.
Utilized data from the Baltimore Longitudinal Study of Aging.
Measured memory performance using the California Verbal Learning Test and lateral ventricle size via structural MRIs.

Main Results:

Recent increases in lateral ventricle size were found to be a significant predictor of subsequent memory decline.
The findings were observed in data spanning ages 60 to 90.
The extended models successfully captured the dynamic interplay between brain structure and cognitive function.

Conclusions:

Recent changes in brain structure, specifically lateral ventricle enlargement, can precede and predict cognitive decline.
Latent difference score models provide a powerful framework for examining change-on-change relationships in longitudinal studies.
These findings have implications for understanding the aging brain and developing interventions for cognitive health.