On estimating true change interrelationships with other variables

This article is concerned with the estimation of indexes of interrelationship between true change in repeatedly assessed latent constructs and other variables. In the social and behavioral sciences this theoretically and empirically important issue arises commonly in research aimed at studying correlates and predictors of growth or decline in a context of a longitudinal research design. A structural equation modeling approach is described that is useful in empirical situations where identifying variables correlated with change in longitudinally followed latent constructs is of interest. The issue of discerning between correlates and predictors of change using the structural equation modeling methodology is discussed. The described approach is used to study correlative aspects of ability growth in a cognitive intervention study (Balteset al., 1986).