As Patrick describes in the first of a series of videos, growth curve models can be useful whenever there is a focus on the analysis of change over time, such as when examining developmental changes, evaluating treatment effects, or analyzing diary data. Although growth models go by a variety of different names, all of these approaches share a common focus on the estimation of individual differences in within-person change over time. Growth curve models estimate smoothed trajectories that are unique to each individual based on the set of observed repeated measures. This results in a collection of individual-specific trajectories that then become the unit of analysis, allowing us to ask such questions as: What is the average trajectory? How much do individual trajectories differ from one another? Can we predict these differences as a function of other individual characteristics?
Patrick discusses these questions within the context of an example on the development of aggressive behavior in children. The data and program files for this example, in SAS, SPSS, Stata, and Mplus, are included along with additional written materials posted for our post-conference workshop Introduction to Growth Curve Modeling.
To see all episodes in this series, see our Growth Modeling playlist.