Description: The Advanced Multivariate Statistical Methods workshop presents a modern approach to multivariate data analysis, focusing on statistical techniques commonly used in empirical research (multilevel/hierarchical linear/mixed models, structural equation models, latent class/finite mixture models) and the commonalities which tie them to the techniques developed and used historically (i.e., Multivariate ANOVA, exploratory factor analysis, canonical correlation analysis, and classical clustering methods). The workshop will teach participants the tenets of modern multivariate thinking: the interplay between assumed statistical distributions (e.g. the multivariate normal distribution) and computationally intensive estimation techniques (maximum likelihood and Bayesian approaches). An emphasis is placed on how modern statistical analysis methods have used these principles to generalize methodology across many disciplines, including education, social and behavioral sciences, and the health fields. At the end of the course, participants will understand how to analyze multivariate data with modern multivariate approaches to test a variety of research hypotheses. A knowledge of linear models is preferable for participants enrolling in the course. Participants who have taken multivariate methods previously are encouraged to enroll and attend as this workshop represents a significant departure from how multivariate statistics have been taught in the past.

Instructor: Jonathan Templin, Associate Professor, University of Georgia

Cost: $525 (includes workshop materials, refreshment breaks, lunch and parking passes each day)

Requirements: Please bring your own laptop computer to participate in this workshop.

Click here to see the complete workshop flyer!

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