Course Description
Introduction to Longitudinal Structural Equation Modeling is a three-day workshop focused on the application and interpretation of structural equation models fitted to repeated measures data. The analysis of longitudinal data (i.e., the repeated measurement of the same cases over time) is fundamental in nearly all areas of social and behavioral science research. There are many structural equation models available for analyzing repeated measures data but the latent curve model is by far the most widely applied and will be the primary focus of this class. Topics include longitudinal designs, linear and non-linear latent curve models, predictors of growth, multivariate latent curve models, and observed and latent multiple group growth models (e.g., mixture models).
Event Details
Start date: December 09, 2020
End date: December 11, 2020
Start time: 09:00 a.m. EST
End time: 05:00 p.m. EST
Venue: Zoom Webinar
Email: info@curranbauer.org
Instructors
Daniel J. Bauer, Ph.D.
Dan Bauer is a Professor and the Director of the L.L. Thurstone Psychometric Laboratory in the Department of Psychology and Neuroscience at the University of North Carolina. He teaches primarily graduate-level courses in statistical methods, for which he has won teaching awards from the University of North Carolina and from the American Psychological Association. Endeavoring to make advanced statistical techniques more accessible, Dan has spent the last 15 years developing and teaching workshops on a variety of topics in both the United States and abroad, including multilevel modeling, mixture modeling, longitudinal data analysis, structural equation modeling, latent curve analysis, missing data analysis, measurement, and integrative data analysis. His research interests lie at the intersection of quantitative and developmental psychology, particularly the development of problem and health-related behaviors over childhood and adolescence. He has published over 65 scientific papers, served as Associate Editor for Psychological Methods, currently serves on the editorial boards of several journals, and has reviewed grants for the National Science Foundation, National Institutes of Health, and the Institute of Educational Sciences. He received an early career award from the American Psychological Association in 2009. For more details, see his academic web page.
Patrick J. Curran, Ph.D.
Patrick Curran is a Professor in the L.L. Thurstone Psychometric Laboratory in the Department of Psychology and Neuroscience at the University of North Carolina at Chapel Hill. Patrick has dedicated much of his career to the teaching and dissemination of advanced quantitative methods and has won teaching awards from UNC and from the American Psychological Association. Over the past 20 years Patrick has taught over 50 national and international workshops on structural equation modeling, multilevel modeling, latent curve analysis, longitudinal data analysis, and general linear modeling. He draws on experiences from his own program of research on high risk child development to guide and inform his quantitative teaching. Patrick’s program of research is primarily focused on the development and evaluation of statistical models of change over time, particularly as applied to studies of adolescent substance use. He has published over 70 scientific papers and chapters and has co-authored a text book on latent curve modeling with Ken Bollen. Patrick has served as Associate Editor for Psychological Methods and currently serves on the editorial boards of seven scientific journals. For more details, see his academic web page.