Journal
EDUCATIONAL PSYCHOLOGIST
Volume 51, Issue 3-4, Pages 354-367Publisher
ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
DOI: 10.1080/00461520.2016.1207176
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Funding
- Fast Start Marsden Grant from Marsden Fund Council from Government [VUW1210]
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Model-based clustering methods, commonly referred to as finite mixture modeling, have been applied to a wide variety of cross-sectional and longitudinal data to account for heterogeneity in population characteristics. In this article, we elucidate 2 such approaches: growth mixture modeling and latent profile analysis. Both techniques are illustrated using motivation data from 2 studies. General strategies for fitting these classes of mixture models are discussed, as are extensions to other applications.
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