Overview

The purpose of this course is to provide students who with an introductory background in the basic principles and applications of hierarchical linear modeling (HLM) in educational research. HLM is a class of models that allows researchers to study a variety of phenomena at different conceptual levels, including individual outcomes nested within classrooms, schools, or other groups (two-level models), and growth in outcomes over time nested within individuals and within classrooms, schools, or other groups (three-level models). The course will review both the conceptual and methodological issues in using hierarchical linear modeling and will provide students with the opportunity to develop and test various HLM models using existing data.

Prerequisites: Introductory statistics (ED214A-C) or equivalent.

For further information: Contact Professor Russell Rumberger by email at russ@education.ucsb.edu.