title: Longitudinal models for studying multivariate changes and dynamics.
abstract: In this paper, we describe a longitudinal modeling approach for examining multivariate changes and dynamics. This technique is based on latent change scores and is executed using a structural equation modeling framework. We provide an overview of the model, describing desirable features for identifying dynamics among multiple processes. We then illustrate its application using empirical data consisting of longitudinal processes and conclude the paper with some potential steps for advancing the modeling possibilities.
authors.affiliation: Department of Psychology, University of California, Davis, Calif., USA.
authors.forename: Emilio
authors.initials: E
authors.lastname: Ferrer
authors.forename: Joseph E
authors.initials: JE
authors.lastname: Gonzales
mesh_terms: D000293:Adolescent; D036262:Empirical Research; D005260:Female; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D008962:Models, Theoretical; D009042:Motivation; D015999:Multivariate Analysis; D012649:Self Concept