Multilevel Theory, Measurement, and Analysis

Catalog description

This course is designed to provide students with an overview of multilevel theory building and testing. Issues to be discussed include: multilevel theory & multilevel constructs, multilevel measurement models including composition and compilation models, data aggregation, aggregation bias, the role of within-group agreement in multilevel measurement, cross-level inference & cross-level bias, cross-level interactions, and multilevel regression models/hierarchical linear models/random coefficient regression models. This course has three goals: 1) To provide students with a broad theoretical understanding of multilevel modeling, 2) To provide students with the technical skills necessary to incorporate multilevel data analytic techniques into their research projects 3) To provide students with a cursory treatment of the mathematical foundations of these topics so that the interested student has the requisite background to pursue advanced training in these areas.