Modeling the co-development of correlated processes with longitudinal and cross-construct effects
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Updated: Mar 13, 2026

Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills
Published on: September 17, 2019
Yaacov Petscher1, Jamie M Quinn1, Richard K Wagner1
1Florida Center for Reading Research, Florida State University.
Abstract:
Conceptualizations of developmental trends are driven by the particular method used to analyze the period of change of interest. Various techniques exist to analyze developmental data, including individual growth curve analysis in observed and latent frameworks, cross-lagged regression to assess interrelations among variables, and multilevel frameworks that consider time as nested within individual. In this paper, we report on findings from a latent change score analysis of oral reading fluency and reading comprehension data from a longitudinal sample of approximately 16,000 students from first to fourth grade. Results highlight the utility of latent change score models compared to alternative specifications of linear and nonlinear quadratic latent growth models as well as implications for modeling change with correlated traits. (PsycINFO Database Record
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