Multilevel studies and multilevel analysis have been
increasingly used in the public health field. This course will discuss
the rationale for multilevel studies and multilevel analysis in public
health as well as differences with other study designs and other
analytical approaches. Although the course will not be heavily
mathematical, the basics of fitting multilevel models for different
types of outcomes as well as the interpretation of estimates obtained
from multilevel models will be reviewed and practiced. Emphasis will be
on conceptual understanding, application and interpretation of
multilevel analysis in the context of urban health research. The course
will also review and critique empirical applications in urban health
research and discuss conceptual and methodological challenges in using
After completing this course, participants will be able to:
To understand the
fundamentals of multilevel studies and multilevel analysis and their
differences with other study designs and analytical approaches.
To be able to fit multilevel models and interpret estimates derived from them.
To be familiar with applications of multilevel analysis in urban health research.
To understand the strengths and limitations of multilevel analysis for urban health research
Prerequisite knowledge: Knowledge of regression analysis (linear, logistic, Poisson) is required for this course.
Instructors: Félice Lê-Scherban, PhD, MPH, assistant professor, Drexel Dornsife School of Public Health; Usama Bilal, MD, PhD, MPH, assistant professor, Drexel Dornsife School of Public Health; and Ana Diez Roux, MD, PhD, MPH, dean of Drexel Dornsife School of Public Health.