A Second-Order Growth Mixture Model for Developmental Research

Abstract

Growth mixture modeling, a combination of growth modeling and finite mixture modeling, is a flexible, exploratory method for identifying and describing between-person heterogeneity in change. In this article we introduce a second-order growth mixture model that combines a longitudinal common factor model, measurement invariance constraints, latent growth model, and mixture model. This approach capitalizes on the benefits of multivariate measurement and the flexibility of mixtures for representing heterogeneity. We describe the model and illustrate its use with multi-reporter longitudinal data from the National Institute of Child Health and Human Development (NICHD) Study of Early Child Care and Youth Development tracking the development of children's externalizing behaviors through elementary school.

ACKNOWLEDGMENT

We would like to thank Jack McArdle, John Nesselroade, Fumiaki Hamagami, Bob Pianta, and our colleagues at the Center for the Advanced Study of Teaching and Learning, the Jefferson Psychometric Laboratory, and the Center for Developmental and Health Research Methodology at the University of Virginia for their helpful comments on this work. The first author would also like to thank John Horn for the conversations we had during the Society of Multivariate Experimental Psychology Conference in 2003 about growth mixture models and possible extensions – one of which was a second-order model. The first author was supported by the National Center for Research in Early Childhood Education, Institute of Education Sciences, U.S. Department of Education (R305A06021). The opinions expressed are those of the authors and do not represent views of the U.S. Department of Education.

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