Methodological and theoretical considerations for the application of latent growth mixture modeling (LGMM) and allied methods such as latent class growth analysis (LCGA) for the identification of heterogeneous populations defined by their pattern of change over time will be presented. Common pitfalls including non-identification, over identification, and issues related to model specification will be discussed as well as the benefits of applying such methods along with the theoretical grounding of such approaches.
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