Growth Curve Analysis in Contemporary Psychological Research

The term “growth curve” is used to describe data where: (1) the same entities are repeatedly observed, (2) the same procedures of measurement and scaling of observations are used, and (3) the timing of the observations is known. Growth curves are now common in many areas of psychological research, and some of these are presented here. The term “growth curve analysis” denotes the processes of describing, testing hypotheses, and making scientific inferences about the growth and change patterns in a wide range of time-related phenomena. In this sense, growth curve analyses are a specific form of the larger set of developmental and longitudinal research methods, but the unique features of growth data permit unique kinds of analyses. Formal models for the analysis of growth curves which have been developed in many different substantive domains are described here in five sections: (1) An introduction to growth curves, (2) linear models of growth, (3) multiple groups in growth curve models, (4) aspects of dynamic theory for growth models, and (5) multiple variables in growth curve analyses. We conclude with a discussion of future issues raised by the current growth models. Keywords: growth curves; latent growth models; longitudinal data analysis; mixed models; multilevel models; nonlinear models

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