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?
To see all episodes in this series, see our Growth Modeling playlist.