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DTSTAMP:20260510T161136Z
DESCRIPTION:Peter Tennant\, PhD\n\nAssociate Professor of Health Data Scien
 ce University of Leeds\n	George Saden Visiting Associate Professor Yale Uni
 versity\n\nThe Seminars in Epidemiology organized by the Department of Epi
 demiology\, Biostatistics and Occupational Health at the McGill School of 
 Population and Global Health is a self-approved Group Learning Activity (S
 ection 1) as defined by the maintenance of certification program of the Ro
 yal College of Physicians and Surgeons of Canada. Physicians requiring acc
 reditation\, please complete the Evaluation Form and send to admincoord.eb
 oh [at] mcgill.ca \n\nWHEN: Monday\, March 30\, 2026\, from 3:30-4:30 p.m.
 \n	WHERE: Hybrid | Onsite at 2001 McGill College\, Rm 1140 | Zoom\n	NOTE: Pe
 ter Tennant will be presenting in-person\n\nAbstract\n\nCausal directed ac
 yclic graphs (DAGs) are among the most widely used causal diagrams. Develo
 ped in the 1980s and 1990s\, with intellectual roots extending back to the
  1920s\, DAGs have become a core part of the modern data scientist’s toolk
 it for planning and interpreting causal analyses of observational data. Ad
 vocates argue that DAGs improve the quality of causal research by increasi
 ng transparency and clarifying common analytical pitfalls. Critics\, howev
 er\, question whether these benefits have truly materialized\, pointing to
  a persistent gap between theoretical promise and real-world practice.\n	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 epidemiol
 ogy. In this talk\, Dr Tennant will revisit the key arguments from that de
 bate and share further reflections on how DAGs can be used more effectivel
 y in epidemiology and health research.\n\nLearning Objectives\n\nAt the en
 d of this talk\, attendees will be able to:\n\n\n	\n		Evaluate the extent to 
 which DAGs have fulfilled their original promises in epidemiological pract
 ice.\n	\n	\n		Recognise common pitfalls in how DAGs are constructed and used i
 n applied health research.\n	\n	\n		Identify priority areas for improving DAG 
 practice in epidemiology and health research.\n	\n\n\nSpeaker Bio\n\nPeter 
 Tennant is an Associate Professor of Health Data Science at the University
  of Leeds and is currently the George Saden Visiting Associate Professor a
 t 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 rev
 iew on the use of directed acyclic graphs to identify confounders in appli
 ed health research\, and his influential work on the challenges of analysi
 ng change scores in observational data. An experienced educator and renown
 ed public speaker\, Dr Tennant regularly presents to diverse audiences aro
 und the world\n
DTSTART:20260330T193000Z
DTEND:20260330T203000Z
SUMMARY:Have Directed Acyclic Graphs (DAGs) Fulfilled Their Promise in Epid
 emiology and Health Research?
URL:https://www.mcgill.ca/channels/channels/event/have-directed-acyclic-gra
 phs-dags-fulfilled-their-promise-epidemiology-and-health-research-371577
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