Introduction to Multilevel Analysis for Urban Health Research

Mon Jun 24 2024 at 09:00 am to Fri Jun 28 2024 at 12:00 pm UTC-04:00

Drexel University Dornsife School of Public Health | Philadelphia

Drexel Urban Health Collaborative Summer Institute
Publisher/HostDrexel Urban Health Collaborative Summer Institute
Introduction to Multilevel Analysis for Urban Health Research
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This course will discuss the rationale for multilevel studies and multilevel analysis in public health.
About this Event

Instructors: , Associate Professor, Drexel Dornsife School of Public Health, , Assistant Professor, Drexel Dornsife School of Public Health

Dates: Monday, June 24 - Friday, June 28

Times: 9:00 a.m. - 12:00 p.m. EST

Format: In-person instruction on campus at Drexel University in Philadelphia

Multilevel studies and multilevel analysis are widely 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 multilevel analysis.

After completing this course, participants will be able to:

  • Understand the fundamentals of multilevel studies and multilevel analysis and their differences with other study designs and analytical approaches.
  • Fit multilevel models and interpret estimates derived from them.
  • Describe applications of multilevel analysis in urban health research.
  • Understand the strengths and limitations of multilevel analysis for urban health research.

Prerequisite knowledge: Knowledge of regression analysis (linear, logistic, Poisson) is required.

Technical requirements: Participants will need access to SAS, Stata, or R (students can choose which; R is publicly available for free).

Continuing Education Credits*: 1.5 CEU or 15 CPH

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Event Venue & Nearby Stays

Drexel University Dornsife School of Public Health, Nesbitt Hall, Philadelphia, United States

Tickets

USD 800.00

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