This article provides an illustration of growth curve modeling within a multilevel framework. Specifically, we demonstrate coding schemes that allow the researcher to model discontinuous longitudinal data using a linear growth model in conjunction with time-varying covariates. Our focus is on developing a level-1 model that accurately reflects the shape of the growth trajectory. We demonstrate the importance of adequately modeling the shape of the level-1 growth trajectory in order to make inferences about the importance of both level-1 and level-2 predictors.
Keywords: coding; growth curve modeling/growth curve model(s); hierarchical linear modeling; multilevel modeling; summer effects; time varying covariates; time varying treatment effects.