Multilevel Modeling

Catalog description

Data in the social and applied sciences are often "nested" or "clustered", with a multilevel structure. For example, jurors are nested within juries, students are nested within classrooms, and repeated measures are nested within persons. This course provides an introduction to the use of multilevel models that take into account such nesting or clustering among observations. Students will learn the basic concepts of multilevel modeling and have the opportunity to apply appropriate analytic techniques to multilevel data in a class project and homework assignments.