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McNeish, Daniel; Harring, Jeffrey R. – Grantee Submission, 2021
Growth mixture models (GMMs) are a popular method to uncover heterogeneity in growth trajectories. Harnessing the power of GMMs in applications is difficult given the prevalence of nonconvergence when fitting GMMs to empirical data. GMMs are rooted in the random effect tradition and nonconvergence often leads researchers to modify their intended…
Descriptors: Growth Models, Classification, Posttraumatic Stress Disorder, Sample Size