ABSTRACT
In this chapter, we present an introduction to multilevel regression and SEM methods that can be used to examine changes in individuals and organizations over time. The multilevel regression approach makes use of repeated observations for each individual defined at Level 1 with differences between individuals specified at Level 2. This requires multiple subject lines for the repeated measures to define the individual’s growth over time in a basic two-level model. In contrast, the SEM approach treats the repeated measures in a manner similar to observed items defining latent intercept and slope factors. Group-level variables (e.g., departments, organizations) can be defined above the individual growth models in either approach. Despite their basic differences in specifying individual and organizational change, both approaches generally yield similar results across a wide variety of longitudinal modeling situations.
