EPIDEMIOLOGIC METHODS 3 Syllabus
Course Learning Objectives
Upon successfully completing this course, students will be able to:
- Link appropriate analytic models with public health research questions and epidemiologic study designs
- Conduct and interpret epidemiologic analyses from a range of multivariable models (including linear, logistic, and Cox regression models)
- Account for the presence of confounding bias using both stratified approaches and multivariable regression
- Identify and critically evaluate different approaches to modeling complex exposures including dose-response relationships & time-varying exposures
- Analyze data for the presence of effect modification
- Critically discuss model limitations with respect to: misspecification, outliers and residual bias
Course DescriptionThird offering in the Epidemiologic Methods sequence. Expands on the presentation of modern epidemiologic inference emphasizing the theory and practice of epidemiologic data analysis. Covers, in detail, detection and analysis of confounding and effect modification using multivariable models in the context of the major epidemiological study designs. Develops an understanding of the underlying principles & assumptions, practical application, and correct interpretation of the epidemiologic results using appropriate multivariable models. Provides experience through laboratory exercises with applying epidemiologic analysis in both infectious and non-infectious disease settings.
Intended AudienceMaster’s, doctoral, and MPH students who will be conducting epidemiologic or clinical research.
Methods of AssessmentWritten assignment(s), Midterm examination, Final examination.
PrerequisitesEpidemiologic Methods 1 and 2 (340.751, 340.752), Statistical Methods in Public Health I and II (140.621, 140.622) or Methods in Biostatistics I and II (140.651, 140.652), and prior or concurrent enrollment in Statistical Methods in Public Health III (140.623) or Methods in Biostatistics III (140.653).
Additional Faculty Notes:
Vittinghoff E, Glidden DV, Shiboski SC, McCulloch CE. Regression Methods in Biostatistics: Linear, Logistic, Survival, and Repeated Measures Models. Springer: 2005.
Rothman KJ, Greenland S, Lash, TL. Modern Epidemiology, 3rd Ed. Lippincott Williams & Wilkins: 20088.
Please see the course Session for a full list of dates and items for this course.
Academic Ethics Code
The code, discussed in the Policy and Procedure Memorandum for Students, March 31, 2002, will be adhered to in this class:
Students enrolled in the Bloomberg School of Public Health of The Johns Hopkins University assume an obligation to conduct themselves in a manner appropriate to the University's mission as an institution of higher education. A student is obligated to refrain from acts which he or she knows, or under the circumstances has reason to know, impair the academic integrity of the University. Violations of academic integrity include, but are not limited to: cheating; plagiarism; knowingly furnishing false information to any agent of the University for inclusion in the academic record; violation of the rights and welfare of animal or human subjects in research; and misconduct as a member of either School or University committees or recognized groups or organizations.
Disability Support ServicesIf you are a student with a documented disability who requires an academic accommodation, please contact Betty H. Addison in the Office of Student Life Services: email@example.com, 410-955-3034, or 2017 E. Monument Street.