The latent growth model (LGM) in structural equation modeling (SEM) may be extended to allow for the modeling of associations among multiple latent growth trajectories, resulting in a multiple domain latent growth model (MDLGM). While the MDLGM is conceived as a more powerful multivariate analysis technique, the examination of its methodological…

Longitudinal models provide researchers with a framework for investigating key aspects of change over time, but rarely is "time" itself modeled as a focal parameter of interest. Rather than treat time as purely an index of measurement occasions, the proposed Time to Criterion (T2C) growth model allows for modeling individual variability…

Due to the complexity of latent transition analysis (LTA) model structure and qualitative decision making in LTA, power analysis has less been reported and studied. Baldwin (2015) and Gudicha, et al., (2016) recently reported results about power analysis in LTA, which included useful information. On the other hand, both studies are limited in the…

Mediation in multi-level data can be examined using conflated multilevel modeling (CMM), unconflated multilevel modeling (UMM), or multilevel structural equation modeling (MSEM). A Monte Carlo study was performed to compare the three methods on bias, type I error, and power in a 1-1-1 model with random slopes. The three methods showed no…