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Daniel McNeish; Jeffrey R. Harring; Daniel J. Bauer – Grantee Submission, 2022
Growth mixture models (GMMs) are a popular method to identify latent classes of growth trajectories. One shortcoming of GMMs is nonconvergence, which often leads researchers to apply covariance equality constraints to simplify estimation, though this may be a dubious assumption. Alternative model specifications have been proposed to reduce…
Descriptors: Growth Models, Classification, Accuracy, Sample Size