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

Kevin J. Grimm, Yang An, John J. McArdle, Alan B. Zonderman, Susan M. Resnick

Research output: Contribution to journalArticle

92 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)268-292
Number of pages25
JournalStructural Equation Modeling
Volume19
Issue number2
DOIs
StatePublished - Apr 2012

Keywords

  • brain
  • dynamic
  • growth
  • latent difference score
  • longitudinal
  • memory

ASJC Scopus subject areas

  • Decision Sciences(all)
  • Modeling and Simulation
  • Sociology and Political Science
  • Economics, Econometrics and Finance(all)

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