Bayesian Multilevel Models
Instructor: Ryan Bakker, University of Georgia
Matrix is located on the 8th floor of Barrows Hall, on the UC Berkeley campus, near Telegraph and Bancroft Avenues, just up the hill from Sather Gate. There are entrances at both ends of the building, but only one of the elevators on the eastern side goes directly to the 8th floor. You can alternatively take the stairs to the 7th floor and walk up the stairs.
This workshop introduces the Bayesian multilevel model framework. Bayesian methods allow for an extremely flexible approach for estimating hierarchical models with a variety different types of dependent variables. Topics covered will be the hierarchical linear model, as well as models with limited dependent variables, summarizing results, in and out of sample predictions, and measures of model fit. No prior knowledge of Bayesian modeling is required but will be beneficial.
Presented as part of the ICPSR Summer Program in Quantitative Methods of Social Research. To register and for further information, visit this page or contact Eva Seto, Associate Director at Social Science Matrix, at evaseto@berkeley.edu.
