A cross-domain model for growth in adolescent alcohol expectancies

Methodologists have recently shown how the methods of individual growth mod eling and covariance structure analysis can be integrated, bringing the fle xibility of the latter to bear on the investigation of inter-individual dif ferences in change. The individual growth-modeling framework uses a pair of hierarchical statistical models to represent: (a) individual status as a f unction of time, and (b) inter-individual differences in true change. Under the covariance structure approach, these level-1 and level-2 models can be reformatted as the "measurement" and "structural" components of the genera l LISREL model with mean structures. Consequently, a covariance structure a nalysis of longitudinal panel data can provide maximum-likelihood estimates for all level-2 parameters. In this article, using longitudinal data drawn from a school-based alcohol prevention trial, we demonstrate how the new a pproach can be used to investigate the inter-relationships among simultaneo us individual changes in two domains - positive and negative alcohol expect ancies - over the course of early to mid-adolescence, for both boys and gir ls. We represent individual change over time in positive expectancies with a piecewise growth model, and in negative expectancies with a straight-line growth model. Then, we use multi-sample covariance structure analysis to a sk whether individual changes in positive and negative expectancies are rel ated to each other and whether the pattern of inter-relationships differs b y gender. Our approach can easily be generalized to more than two domains a nd has a variety of other advantages that we document in the discussion.