MESA8450 · Education
Lynch School of Education & Human Development
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.
Course experience
Averages use the original five-point historical evaluation scale.
Organization
— / 5
How well the course was organized
Challenge
— / 5
How intellectually challenging students found it
Attendance
— / 5
How necessary attendance was
Assignments
— / 5
How helpful assignments were
Weekly effort
—
hours per week
Estimated from the original workload response buckets. Individual sections may differ.
Instructor options
Ratings below reflect only recovered evaluations connected to this course.
Across time
Section-level results available in the recovered archive.
Spring 2025
1 sectionSpring 2024
1 section