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EPID 652: Advanced Epidemiologic Methods and Data Analysis

Course Prerequisites:

EPID 651 and BIOS 554, or equivalent

Course Description:

This course focuses on development of analytical strategies for data analysis guided by epidemiologic principles. Specific statistical modeling will be tailored for analysis of data from cross-sectional, case-control and cohort studies with emphases on effect estimates, causal inference, controlling for confounding, and assessment of interaction and mediation effects. Course topics cover applied multivariate analysis including logistic regression, log-binomial regression, Cox proportional hazards model, Poisson regression, multilevel and path analytical model.

Course Goal:

The goal of this class is to provide epidemiologic principles and statistical techniques that are commonly used in advanced epidemiologic research. After the course, students will be of confident in the application of advanced modeling techniques in analysis of epidemiologic data and interpretation of findings.

Objectives:

By the end of the course, the student will

  1. Develop analytic strategies for various study designs, guided by the principles of epidemiology.
  2. Understand the rationale and assumptions underlying the major statistical techniques used to analyze data from epidemiological studies.
  3. Describe strengths, limitations, and issues pertinent to the proper application of these techniques.
  4. Explain how interactions/effect modification, confounders and dose-response relationships among variables are examined.
  5. Utilize appropriate methods of analysis to account for interaction/effect modification, confounding, and mediation effects.
  6. Compute and interpret odds ratios, prevalence ratio, relative risks, rate ratio, hazard ratio, and their confidence intervals.
  7. Demonstrate competency in using SAS to perform data analysis for cross-sectional, case-control, and cohort studies.

Required Textbooks:

  1. Rothman KJ, Greenland S, Lash TL. Modern Epidemiology, 3 rd edition. Lippincott Williams & Wilkins, Philadelphia, PA, 2008.
  2. Logistic Regression: A self-learning text (3rd Edition) D.G. Kleinbaum and M. Klein. Springer, 2010
  3. Handouts will be on canvas or distributed in class if necessary

Supplemental text:

  1. Szklo M and Nieto FJ. Epidemiology: Beyond the Basics, 3 rd edition. Jones & Bartlett Learning, Burlington, MA, 2014.
  2. Woodward M. Epidemiology: Study Design and Data Analysis, 2 nd edition, Chapman & Hall/CRC, Boca Raton, FL, 2005.

Course Format

Course sessions will entail a combination of lectures, discussions, problem sets, and in-class activities in the lab sessions. Based on by our teaching philosophy and experience, we believe active student participation is essential in success.

There are three parts in the 3-credit course, (1) overview of epidemiologic designs, e.g., cross-sectional, case- control, and cohort studies; (2) application of specific statistical methods in a specific study design; (3) use of SAS statistical software to perform data analysis. The first two items will be covered during classroom lectures and the third part will involve SAS programming.

Course Evaluation

Final grades will be determined by scores of class participation, Exam 1, homework assignments, and Exam 2.

Grading