Growth curve modeling has become a mainstay in the study of development. In this article we review some of the flexibility provided by this technique for describing and testing hypotheses about: (1) intraindividual change across multiple occasions of measurement, and (2) interindividual differences in intraindividual change. Through empirical example we demonstrate how linear, quadratic, latent basis, exponential, and multiphase versions of the model can be specified using commonly available SEM/multilevel modeling software and illustrate and discuss how results are obtained and interpreted. Particularly, we underscore the "developmental theory" articulated by each model.
All Science Journal Classification (ASJC) codes
- Social Psychology
- Developmental and Educational Psychology
- Social Sciences (miscellaneous)
- Developmental Neuroscience
- Life-span and Life-course Studies