This chapter provides growth mixture models into a nonlinear framework and examines patterns of cognitive development across the lifespan. It presents the work on nonlinear growth mixture models to include models based on structured curves, growth models based on latent difference scores and related multivariate models. The chapter outlines the latent growth modeling with consideration for nonlinear, multiple group, and multivariate growth models, a short introduction to growth mixture modeling, and an application of nonlinear growth mixture models to lifespan cognitive development data. In the data file the measurements are grouped into common units of time/age. The latent difference score growth curves can model a series of nonlinear shapes and allow for the evaluation of time-dependent influences on the change in the variable of interest. Some of the possibilities in cognitive aging are subpopulations of participants with a differential decline in late adulthood or subpopulations with a stunt in growth during adolescence.
|Original language||English (US)|
|Title of host publication||Longitudinal Models in the Behavioral and Related Sciences|
|Publisher||Taylor and Francis|
|Number of pages||28|
|State||Published - Jan 1 2017|
ASJC Scopus subject areas
- Social Sciences(all)