91丝瓜视频

Peter Tennant, PhD

Associate Professor of Health Data Science University of Leeds
George Saden Visiting Associate Professor Yale University

The Seminars in Epidemiology organized by the Department of Epidemiology, Biostatistics and Occupational Health at the 91丝瓜视频 School of Population and Global Health is a self-approved Group Learning Activity (Section 1) as defined by the maintenance of certification program of the Royal College of Physicians and Surgeons of Canada. Physicians requiring accreditation, please complete the Evaluation Form and send to admincoord.eboh [at] mcgill.ca

WHEN: Monday, March 30, 2026, from 3:30-4:30 p.m.
WHERE: Hybrid | Onsite at 2001 91丝瓜视频 College, Rm 1140 |
NOTE: Peter Tennant will be presenting in-person

Abstract

Causal directed acyclic graphs (DAGs) are among the most widely used causal diagrams. Developed in the 1980s and 1990s, with intellectual roots extending back to the 1920s, DAGs have become a core part of the modern data scientist鈥檚 toolkit for planning and interpreting causal analyses of observational data. Advocates argue that DAGs improve the quality of causal research by increasing transparency and clarifying common analytical pitfalls. Critics, however, question whether these benefits have truly materialized, pointing to a persistent gap between theoretical promise and real-world practice.
At the 2024 World Congress of Epidemiology, Dr Peter Tennant (University of Leeds) and Prof Margarita Moreno Betancur (University of Melbourne) took part in a debate on whether DAGs have fulfilled their promise in epidemiology. In this talk, Dr Tennant will revisit the key arguments from that debate and share further reflections on how DAGs can be used more effectively in epidemiology and health research.

Learning Objectives

At the end of this talk, attendees will be able to:

• Evaluate the extent to which DAGs have fulfilled their original promises in epidemiological practice.

• Recognise common pitfalls in how DAGs are constructed and used in applied health research.

• Identify priority areas for improving DAG practice in epidemiology and health research.

Speaker Bio

Peter Tennant is an Associate Professor of Health Data Science at the University of Leeds and is currently the George Saden Visiting Associate Professor at Yale University. Trained as an epidemiologist, his research focuses on adapting and translating contemporary causal inference methods into health and social science. He is best known for his landmark meta-scientific review on the use of directed acyclic graphs to identify confounders in applied health research, and his influential work on the challenges of analysing change scores in observational data. An experienced educator and renowned public speaker, Dr Tennant regularly presents to diverse audiences around the world