Latent Variable Growth Modeling with Multilevel Data

Abstract

Growth modeling of multilevel data is presented within a latent variable framework that allows analysis with conventional structural equation modeling software. Latent variable modeling of growth considers a vector of observations over time for an individual, reduing the two-level problem to a one-level problem. Analogous to this, three-level data on students, time points, and schools can be modeled by a two-level growth model. An interesting feature of this two-level model is that contrary to recent applications of multilevel latent variable modeling, a mean structure is imposed in addition to the covariance structure. An example using educational achievement data illustrate the methodology.