Growth mixture modeling (GMM) is a methodological tool used to represent heterogeneity in longitudinal datasets through the identification of unobserved subgroups following qualitatively and quantitatively distinct trajectories in a population. These growth trajectories or functional forms are informed by the underlying developmental theory, are…

This dissertation informed researchers about the performance of different level-specific and target-specific model fit indices in Multilevel Latent Growth Model (MLGM) using unbalanced design and different trajectories. As the use of MLGMs is a relatively new field, this study helped further the field by informing researchers interested in using…