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Methodological Advances in Longitudinal Mixture Modeling
Sun, April 11, 2:30 to 4:00pm EDT (2:30 to 4:00pm EDT), Division D, Division D - Section 2 Paper and Symposium SessionsSession Type: Symposium
Abstract
This organized symposium brings together a set of papers that focus on a range of issues related to the development and application of mixture models in longitudinal contexts. While mixture models are growing ever more popular in educational research, methodology for longitudinal and multilevel mixture 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 longitudinal mixture models, including latent transition analysis, growth mixture modeling, mixture regression, and latent class analysis with distal outcomes, while providing practical guidance and concrete illustrations regarding the application of these advanced techniques in real data settings.
Sub Unit
Chair
Papers
Understanding Change in Latent Transition Analysis Models Using Auxiliary Variables - Karen L. Nylund-Gibson, University of California - Santa Barbara; Dina Naji Arch, University of California - Santa Barbara; Adam Garber, University of California - Santa Barbara
Examining Residual Correlations in Latent Transition Analysis: A Simulation Study - Ryan Grimm, SRI International; Karen L. Nylund-Gibson, University of California - Santa Barbara
Moderation With a Latent Class Variable: Specification, Visualization, and Specification - Dina Naji Arch, University of California - Santa Barbara; Karen L. Nylund-Gibson, University of California - Santa Barbara; Marsha M. Ing, University of California - Riverside
Residual-Based Algorithm for Detecting Mixtures in Latent Growth Models - Katerina M. Marcoulides, University of Minnesota; Laura TRINCHERA, NEOMA Business School
Examination of School Climate and Distal Outcomes Using the Three-Step Method - Kathleen McGrath, Charlotte-Mecklenburg Schools