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140.623.02 Statistical Methods in Public Health III

3rd term
4 credits
Academic Year:
2014 - 2015
East Baltimore
Class Times:
  • Tu Th,  10:30 - 11:50am
Auditors Allowed:
Yes, with instructor consent
Grading Restriction:
Letter Grade or Pass/Fail
John McGready
Course Instructors:



Presents use of generalized linear models for quantitative analysis of data encountered in public health and medicine. Specific models include analysis of variance, analysis of covariance, multiple linear regression, logistic regression, and Cox regression.

Learning Objectives:

Upon successfully completing this course, students will be able to:

  1. Critique a proposed public health hypothesis to determine its suitability for testing using regression methods and the available data
  2. Formulate and correctly interpret a multivariable linear, logistic or survival regression model to estimate a health effect while minimizing confounding and identifying possible effect modification
  3. Appreciate the importance of relying upon many regression models to capture the relationships among a response and predictor in observational studies
  4. Create and interpret regression diagnostic plots and adjusted variable plots that display the relationships among an outcome and multiple predictors
  5. Create and interpret tables of regression results including unadjusted and adjusted estimates of coefficients with confidence intervals from many models
  6. Employ life-table methods and Poisson regression models to describe associations between risk factors and grouped survival data
  7. Employ Kaplan-Meier and Cox proportional hazards regression models to describe associations between risk factors and time to event data.
  8. Use statistical methods for inference to correctly interpret regression coefficients and their confidence intervals in order to draw valid public health inferences from data
  9. Use the statistical analysis package Stata to perform univariate, bivariate and multivariable regression models and to document and archive the steps of the statistical analysis by creating a Stata do-file
Methods of Assessment:

Student evaluation based on problem sets and exams.

Enrollment Restriction:

For PhD, ScM and MHS degree candidates in departments to be determined

Instructor Consent:

Consent required for some students

Consent Note:

Consent required for non-PH students

For consent, contact:

Special Comments:

One 90-minute lab per week, lab is 140.923. As soon as you register for the course, please also register for one section of 140.923. Course Materials Fee is $40.00. Students will use the Stata statistical analysis software for problem sets; Stata is installed for their use in the computer labs and also available for purchase via the Stata educational GradPlan.