Using individual growth curves to model reading fluency

Abstract

There are a wide variety of longitudinal models which focus on different aspects of the longitudinal or change process and make very different assumptions about the underlying processes that influence the stability or change in data across time. In this chapter, we focus on one specific type of longitudinal model: The individual growth model. Growth curve models provide researchers with a method to investigate systematic growth (or decline) in outcomes across time. Growth curve models allow for the estimation of growth parameters (such as the initial status and the growth rate) for each individual in the study. Using growth models, researchers can estimate distinct model-implied growth rates for each individual in the study and can explore both between- and within-person differences in change across time. Growth curve models can be estimated using either multilevel (mixed) or structural equation models (SEM). Although most basic growth models can fit in either framework, each of the techniques provides certain advantages. Therefore, in this chapter, we provide a brief introduction to individual growth curve modeling in both the multilevel and structural equation modeling frameworks, and demonstrate the approaches using an applied example.