A Statistical Power Comparison from Multivariate and Univariate Latent Growth Models with Incomplete Data

Latent growth modeling (LGM) is widely used to examine group differences in developmental trajectories in educational research. With multiple outcomes of interest, a multiple-domain latent growth model (MDLGM) can be applied to account for associations among growth trajectories from the outcomes. While the MDLGM is conceived as a more powerful multivariate analysis technique when compared with univariate LGM, the examination of its methodological performance is very limited. Henceforth, this study compared the statistical power of the MDLGM and separate univariate LGMs via a simulation study with a two-group, two-domain design. Results indicated that the MDLGM and the set of LGMs showed largely comparable power, with a small advantage for the MDLGM under conditions of weak inter-domain correlation and small group differences and showed reduced power as missingness increased. These findings provide educational researchers with a guideline for model selection in longitudinal studies with multiple outcomes.