Nonlinear Mixed-Effects Growth Models: A Tutorial Using saemix in R

• In Event: Methodological Considerations and Guidance for Estimating Longitudinal/Growth Models

Abstract

Modeling growth and evaluating the predictors of growth parameters are educationally relevant tasks. When growth follows a sigmoidal shape, the Logistic, Gompertz, and Richards nonlinear growth curves are plausible. These functions have parameters that control total growth, overall rate of change, and point of greatest growth. Variability in growth parameters across individuals can be explained by covariates in a mixed model framework. The purpose of this tutorial is to provide analysts with a brief introduction to these growth curves and demonstrate their application using the saemix package in R with simulated data to answer applied research questions. Enough code is provided in-text to describe how to execute the analyses with the complete code provided in the Appendix.

Author

• Peter Boedeker, Baylor College of Medicine