Advanced Epidemiological Methods Seminar, 30 July-2 August 2018 Deadline Extended

Posted on Thu, Dec 14 2017 22:43:00



Dr. Matthew Fox of the Department of Epidemiology and the Center for Global Health and Development at Boston University will be presenting an intensive 4-day course on advanced epidemiological methods at Stellenbosch University under the auspices of the South African DST-NRF Centre for Epidemiological Modeling and Analysis (SACEMA), 30 July-2 August 2018. The course will take place from 9:00 to 15:30 daily at the Africa Centre for HIV/AIDS Management, C/O Banhoek and Joubert Street, Stellenbosch University.

  • The deadline for registration has been extended to 30June 2018
  • For participants within South Africa, the course fee is R7000.
  • For international participants, the fee is 600 € . Note: Full payment must be processed prior to start of the course.
  • The fee includes refreshments, lunches, some social events, and a non-refundable registration fee of R1200, for South African participants, or 110 € for international participants.

The costs of accommodation, breakfast, and dinner are not included. Short-term accommodation is in high demand, so best to book early. Useful websites include AirbnbTripAdvisor, Sleeping out and

For enquiries contact Assistant Director for Training, Gavin Hitchcock:, copied to Matthew Fox:


Matthew Fox, DSc, MPH, is Associate Professor in the Center for Global Health & Development and in the Department of Epidemiology at Boston University. Dr. Fox joined the Center in 2001. Before joining Boston University, he was a Peace Corps volunteer in the former Soviet Republic of Turkmenistan. His research interests include treatment outcomes in HIV-treatment programs, infectious disease epidemiology (with specific interests in HIV, pneumonia, and malaria), and epidemiological methods. Dr. Fox is currently working on ways to improve retention in HIV-care programs in South Africa from the time of testing HIV-positive through long-term treatment. Dr. Fox also does research on quantitative sensitivity analysis and recently co-authored a book on these methods, Applying Quantitative Bias Analysis to Epidemiologic Data. He currently teaches a third-level epidemiological methods class. Dr. Fox is a graduate of the Boston University School of Public Health with a master's degree in epidemiology and biostatistics and a doctorate in epidemiology.

Course Overview
Introductory and intermediate courses in epidemiological methods teach students the concepts needed to begin a career conducting valid epidemiological research; however these courses typically only briefly cover the causal models that should underlie the design of valid epidemiological studies. We will use these models as a jumping-off point to begin rethinking what we have already learned and to go further in our understanding of basic concepts of measures of effect, confounding, misclassification and selection bias. From there we will begin to question the implications of various sources of bias in our studies and we will work through novel methods and approaches for doing more than simply speculating about these biases. We will then finish by exploring the basic statistics used in epidemiological research and we will correct misunderstandings about what these statistics can tell us.

Throughout the course we will focus on the core concepts of validity and precision and will further develop our understanding of these central concepts. We will emphasize the development of skills that every doctoral level epidemiologist should have, skills that are both practical and marketable. Note that this course is not offered for any credit. It is a course designed to help doctoral level and advanced master's students advance their skills.

A rough sketch of the session titles for each day has been attached but is subject to change.

Students are expected to prepare fully for class by reading the material ahead of time. There will be several readings per day, listed below. The readings for this course are challenging. You will not understand everything you read and you will need to read the articles more than once before coming to class. You will struggle if you wait until the last minute or do not read the material. The class can only function if you are prepared and have challenged yourself to think about the material. Come to class with questions about what you do not understand.

Day 1

  • Ioannidis JP. Why most published research findings are false. PLoS Med 2005;2(8):e124.
  • Greenland S and Robins JM. Identifiability, exchangeability, and epidemiological confounding. Int J Epidemiol 1986;15:412-418

Day 2

  • Greenland S, Pearl J, and Robins JM. Causal diagrams for epidemiologic research. Epidemiology 1999;10:37-48.
  • Hernan MA, Brumback B, Robins JM. Marginal structural models to estimate the causal effect of zidovudine on the survival of HIV-positive men. Epidemiology 2000;11(5):561-570.

Day 3

  • Rothman KJ. Modern Epidemiology, 1st Edition. Chapter 15 - Interaction between Causes. Little, Brown, and Company, Boston, MA: 1986. pp 311-326.
  • Jurek AM, Greenland S, Maldonado G et al. Proper interpretation of non-differential misclassification effects: expectations vs observations. Int J Epidemiol 2005;34(3):680-687.

Day 4

  • Greenland S. Randomization, Statistics, and Causal Inference. Epidemiology 1990;1:421-429.
  • Poole C. Low P-Values or Narrow Confidence Intervals: Which Are More Durable? Epidemiology 2001;12(3): 291-294.