Figure 1. Schematic Display of Models Tested in Parallel Process Growth Mixture Models.

Notes: Only the latent growth parameters are displayed here for ease of presentation. Labels a-d represent growth factor parameter variance estimates. Labels e-h represent growth factor parameter covariance estimates. Five different unconditional parallel process growth mixture models (GMM) were estimated that differed in their patterns of constraints placed upon these parameters. GMM-1 constrained parameters a-h to be zero across trajectory classes. GMM-2 freely estimated parameters a-h, but these parameters were constrained to be equal across classes. GMM-3 freely estimated parameters a-h; however, parameters a-d were allowed to vary across classes, whereas parameters e-h were constrained to be equal across classes. GMM-4 freely estimated parameters a-h; however, parameters a-d were constrained to be equal across classes, whereas parameters e-h were allowed to vary across classes. GMM-5 freely estimated parameters a-h and permitted each parameter to vary across classes.