Course Description
Focuses on applications of hierarchical linear and nonlinear models (HLM). Reviews the logic and estimation principles of HLM. Two-level models are illustrated, including estimating organizational effects on individuals and examining individual change over time. Generalizations to three-level models and to nonlinear models for discrete outcomes are considered.
Athena Title
SOCI MULTILEVEL MOD
Prerequisite
SOCI 6630 or permission of department
Grading System
A - F (Traditional)
Course Objectives
Students will be required to learn software for the analysis of hierarchical data. Students will develop the practical skills to apply statistical techniques discussed in class through a series of computer assignments. These assignments reinforce understanding of basic concepts as students learn how to diagnose and interpret a variety of HLM models.
Topical Outline
1. The Logic of Hierarchical Linear Models 2. Creating Input Files for HLM 3. The Basic Two-Level Model 4. Applications in Organizational Research 5. The Analysis of Individual Change (growth models) 6. Three-level Models 7. Hierarchical Generalized Linear Models