Download printable overview of the workshop here!
Session organisers: Locksley Messam1, BSc, DVM, PhD and Hsin-Yi Weng2, BVMS, MPH, PhD
1 Section: Herd Health and Animal Husbandry, School of Veterinary Medicine, University College Dublin, Dublin, Ireland (email@example.com)
2 Department of Comparative Pathobiology, College of Veterinary Medicine, Purdue University, West Lafayette, Indiana, USA (firstname.lastname@example.org)
Directed Acyclic Graphs (DAGs) are widely accepted by the epidemiologic community as useful tools for combatting confounding in observational studies. They can be used in both the design and analytic phases of a study and provide a visual, transparent and logically coherent way of identifying potential confounders of exposure-outcome relationships. This includes the identification of variables which meet traditional criteria for confounding but will, if adjusted for, cause bias in estimates.
We assume that participants will be familiar with:
Part I: Participants will initially be introduced to the role of causal assumptions in making inferences from observational studies, the terminology of DAGs, their construction, interpretation and applications.
Part II: We will then split into groups of 4-5 persons and work on the construction, interpretation and solution of DAGs using provided examples. The focus will be on practice in identifying appropriate subsets of variables for confounder control.
At the end of this workshop, each participant should:
Locksley’s research interests include: Human-Animal interactions and their effects on human health and wellbeing, principles and applications of diagnostic test interpretation in veterinary medicine, and the application of epidemiologic methods and approaches used in other fields to veterinary medicine. He enjoys teaching and is currently a Lecturer at the University College Dublin where he teaches a course on epidemiology to veterinary students and participates in epidemiology instruction in the MPH programme.
Hsin-Yi‘s main research interests are in applying epidemiologic methods to studies promoting animal health and welfare, human-animal interactions, and public health. She is an Assistant Professor of Clinical/Analytical Epidemiology at Purdue University and currently teaches a DVM epidemiology course and a graduate level course focusing on design and analysis of epidemiological studies.