Different growth patterns are quite possible when data include sources of population heterogeneity. The sources of growth heterogeneity may be observed or latent. This article discusses how multidimensional scaling (MDS) can, in the framework of growth mixture modeling, provide an exploratory technique for identifying potential latent growth profiles, which may be indicative of growth associated with population heterogeneity. MDS can be used to examine the likelihood that latent growth profiles represent either known or unknown subgroups in the population. In addition, the association between latent growth profiles and other covariates can be studied. Characteristics of MDS profile analysis are described in comparison with other techniques commonly used for growth mixture modeling. A step-by-step analysis of two empirical examples illustrates how the MDS profile analysis provides an alternative tool for identifying growth trends and studying individual differences with respect to these growth trends.
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