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

Latent difference score models (e.g., McArdle & Hamagami, 2001 ) are extended to include effects from prior changes to subsequent changes. This extension of latent difference scores allows for testing hypotheses where recent changes, as opposed to recent levels, are a primary predictor of subseq...

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Bibliographic Details
Published in:Structural equation modeling 2012-04, Vol.19 (2), p.268-292
Main Authors: Grimm, Kevin J., An, Yang, McArdle, John J., Zonderman, Alan B., Resnick, Susan M.
Format: Article
Language:English
Subjects:
Aging
Aging (Individuals)
Brain
Data collection
Difference Scores
dynamic
Evaluation Research
Federal Aid
Geriatrics
growth
Hypothesis Testing
latent difference score
Latent Variables
longitudinal
Longitudinal Studies
Maryland
Measurement Techniques
Memory
Older Adults
Predictor Variables
Scores
Statistical Analysis
Structural Equation Models
Verbal learning
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Summary:Latent difference score models (e.g., McArdle & Hamagami, 2001 ) are extended to include effects from prior changes to subsequent changes. This extension of latent difference scores allows for testing hypotheses where recent changes, as opposed to recent levels, are a primary predictor of subsequent changes. These models are applied to bivariate longitudinal data collected as part of the Baltimore Longitudinal Study of Aging on memory performance, measured by the California Verbal Learning Test, and lateral ventricle size, measured by structural MRIs. Results indicate that recent increases in the lateral ventricle size were a leading indicator of subsequent declines in memory performance from age 60 to 90.
ISSN:1070-5511
1532-8007
DOI:10.1080/10705511.2012.659627