Courses

Multilevel Models

June 24 - June 28, 2024
1:30 p.m. – 5:00 p.m.
2 credits
Course Number: 140.607.79 (synchronous online)
                                      

"Dr. Zhu was very clear in explaining the process of model construction. The course content makes a complicated model easy to understand. The code of STATA provided by the course is also friendly for non-STATA users."—Student, 2023

"The instructor was very knowledgeable about multilevel modeling and was very invested in helping students understand these concepts."—Student, 2022

Course Instructor:

Description:

Gives an overview of "multilevel statistical models" and their application in public health and biomedical research. Multilevel models are regression models in which the predictor and outcome variables can occur at multiple levels of aggregation: for example, at the personal, family, neighborhood, community and regional levels. They are used to ask questions about the influence of factors at different levels and about their interactions. Multilevel models also account for clustering of outcomes and measurement error in the predictor variables. Students focus on the main ideas and on examples of multi-level models from public health research. Students learn to formulate their substantive questions in terms of a multilevel model, to fit multilevel models using Stata during laboratory sessions and to interpret the results.

Student Evaluation: Final exam

Learning Objective:

Upon successfully completing this course, students will be able to: 1) prepare graphical and tabular displays of multilevel data that effectively communicate the patterns of scientific interests; 2) conduct statistical analyses of clustered data by use of multilevel models; 3) interpret parameters of multilevel statistical models; 4) fit multilevel models by use of statistical software packages.

Location: Baltimore

Prerequisite: Previous experience with regression analysis is required.

Grading Options: Letter Grade or Pass/Fail

Course Materials: