ED 861 Multilevel Regression Models (Spring: 3)

Prerequisite: ED/PY 667
Cross Listed with PY861
Offered Biennially
This course introduces students to multilevel regression modeling (aka hierarchical models or mixed effects models) for analyzing data with a nesting or hierarchical structure. We discuss the appropriate uses of multilevel regression modeling, the statistical models that underpin the approach, and how to construct models to address substantive issues. We consider a variety of types of models, including random intercept, and random slope and intercept models; models for longitudinal data; and models for discrete outcomes. We cover various issues related to the design of multilevel studies, model building and the interpretation of the output from HLM and SPSS software programs.
Laura O'Dwyer

Last Updated: 20-JUN-13