It has been demonstrated that the individual variation in the level and rate of learning for a cohort of students over time can be estimated by hierarchical linear models. Models of this type can also be estimated using widely available structural modeling software, which provides a flexible framework for model explorations, including the use of latent variables purged of the influence of measurement error. A growth model is developed that can also be viewed as a structural model with latent variables. As an illustration of the structural modeling approach, data from a study by G. L. Williamson and others (1991) are reanalyzed, working with the reading achievement scores of 278 females. Two figures illustrate the analysis. (SLD)