ABSTRACT
This chapter presents an introduction to multilevel regression and structural equation modeling (SEM) methods that can be used to examine changes in individuals and organizations over time. First, it briefly outlines several ways of collecting and analyzing longitudinal data. While there are a number of ways to examine longitudinal data, the chapter next introduce two broad approaches for examining changes within individuals and groups. The first approach focuses on estimating growth or change from the perspective of random-coefficients multilevel modeling, which can be easily defined using the Mplus software. The second approach focuses on the use of latent variables, which are common in SEM, for examining individual and organizational change. The structural part of the SEM analysis can then be used to investigate the effects of covariates or other latent variables on the latent change factors. The SEM approach makes use of latent variables; it has been referred as latent growth curve analysis, latent change analysis, or latent growth models.
