Introduction to Individual Growth Curve Analysis

Abstract

Many questions of interest in child psychiatry, psychology, and neuropsychology are questions about change and its prediction. For instance, do children who suffer closed-head injuries at an early age recover more slowly and show greater long-term deficits than children injured at a later age? Do initial deficits in verbal or spatial functioning lead to deterioration in adaptive functioning after injury? Do characteristics of the child moderate the effectiveness of interventions for attention deficit disorder? To address such questions, researchers frequently employ longitudinal designs that lend themselves naturally to addressing questions about change and its prediction. Unfortunately, some traditional statistical models for longitudinal data are unsatisfactory for characterizing change at the individual level and for studying correlates of change. Consequently, after expending considerable effort to collect longitudinal data, researchers often fail to satisfactorily address questions about change in their analyses. The limitations of many traditional statistical models have led to increased interest in the behavioral sciences in the use of individual growth models for measuring change and examining correlates of change.