140.607.11
Multilevel Models
Location
East Baltimore
Term
Summer Institute
Department
Biostatistics
Credit(s)
2
Academic Year
2019 - 2020
Instruction Method
TBD
Start Date
Monday, June 24, 2019
End Date
Friday, June 28, 2019
M, Tu, W, Th, F, 1:30 - 4:50pm
Auditors Allowed
No
Available to Undergraduate
No
Grading Restriction
Letter Grade or Pass/Fail
Course Instructor(s)
Contact Name
Frequency Schedule
Every Year
Resources
Prerequisite
Previous experience with regression analysis is required.
Gives an overview of "multilevel models" and their application in public health and biomedical research. Multilevel models are statistical regression models for data that are clustered in some way, violating the usual independence assumption. Typically, the predictor and outcome variables occur at multiple levels of aggregation (e.g., at the personal, family, neighborhood, community and/or regional levels). Multilevel models account for the clustering of the outcomes and are used to ask questions about the influence of factors at different levels and about their interactions. Students focus on the main ideas and on examples of multilevel 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.
Learning Objectives
Upon successfully completing this course, students will be able to:
- Prepare graphical and tabular displays of multilevel data that effectively communicate the patterns of scientific interests
- Formulate their substantive questions in terms of a multilevel models
- Interpret parameters of multilevel statistical models
- Fit multilevel models using the Stata statistical software packages
Methods of Assessment
This course is evaluated as follows:
- 40% Final Exam
- 15% Lab Assignments
- 15% Lab Assignments
- 15% Lab Assignments
- 15% Lab Assignments