Latent variable growth within behavior genetic models.

The purpose of this paper is to introduce one kind of latent-variable structural-equation model for multivariate longitudinal data which includes behavioral genetic components. A generic structural-equation model termed RAM (McArdle, J. J. and McDonald, R. P. (1984). Br. J. Math. Stat. Psychol . , 37:239~251.) is used to define the univariate twin design, including both covariances and means. This model is extended to multivariate form using a latent-variable growth-curve model recently presented by W. Meredith and J. Tisak [(1984). "Tuckerizing" curves. Psychometric Society Annual Meetings]. The model presented herein further permits hypothesis testing of various biometric models of the sources of these individual differences in latent growth. Aspects of this model are illustrated using the LISREL algorithm [Jfreskog, K. G. and SOrbom, D. (1979). Advances in Fac to r Analysis and Structural Equat ion Models, Abt Books, Cambridge, Mass.] and longitudinal twin data on early childhood abilities [Wilson, R. S. (1983). Child Dev. 54:298-316].