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 performance is very limited. Hence, the present study compared the power of the MDLGM with that of a set of LGMs for detecting group differences in growth rates over time using a Monte Carlo study via a two-group and two-domain design. The results indicated that there were different scenarios where the power rates for MDLGM were greater and that of the set of LGMs (or vice versa) due to a joint function of the two domains' group difference effect sizes and the intercorrelation between two domains.