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Session Type: Symposium
This symposium brings together a set of papers that focus on advanced applications of mixture models in educational and early development research. The use and development of mixture models has received attention over the years, methodology for the use of these models is rapidly evolving, continually overturning the prescribed analytic strategies for applied researchers. This session is designed to showcase some of the latest methodological advances in mixture models, including latent transition analysis, mixture regression, intervention studies, and framing mixture modeling as a social justice tool. This collection of papers provides practical guidance and concrete illustrations regarding the application of these techniques in real data settings.
Latent Transition Analysis for Intervention Students - Adam Garber, University of California - Santa Barbara; Ryan Grimm, SRI International; Karen L. Nylund-Gibson, University of California - Santa Barbara
Mixture Regression Analysis: The Effects of Anti-Bullying Interventions on Bullying Behavior - Hye-Young Yun, University of California - Los Angeles; Karen L. Nylund-Gibson, University of California - Santa Barbara; Christina Salmivalli
Meta-Analysis of Monte Carlo Simulations Examining Class Enumeration Accuracy With Mixture Models - Tiffany A. Whittaker, University of Texas at Austin; Jihyun Lee, University of North Texas; Devin Dedrick; Christina Munoz
The Use of Regression Mixture Modeling With a Social Justice Lens - Dina Naji Arch, University of California - Santa Barbara; Karen L. Nylund-Gibson, University of California - Santa Barbara
Random Intercepts Latent Transition Analysis: Illustration Using the Social Emotional Health Survey - Delwin Carter, University of California - Santa Barbara; Karen L. Nylund-Gibson, University of California - Santa Barbara; Michael J. Furlong, University of California - Santa Barbara; Erin Dowdy, University of California - Santa Barbara
Using the Ant Colony Optimization Algorithm for Automated Specification of Mixture Models - Walter L. Leite, University of Florida; Zuchao Shen, University of Georgia; Karen L. Nylund-Gibson, University of California - Santa Barbara; Katerina M. Marcoulides, University of Minnesota