From a Blank Canvas to a Transparent Causal Diagram: How to Draw and Use Directed Acyclic Graphs (DAGs)
Speakers
Jay J Park, PhD, McMaster University, Vancouver, BC, Canada; Rebecca Metcalfe, BA, MA, PhD, CCS, Calgary, AB, Canada
With increasing emphasis on real-world evidence, causal inference methods are being used more often to support regulatory, payer, and health technology assessment decisions. When using these methods, both NICE and the FDA recommend directed acyclic graphs (DAGs) to visually outline, and make explicit, assumptions about causal relationships between variables. Join us for an interactive session on the ins and outs of constructing DAGs to strengthen causal analyses.
Code
026
Topic
Epidemiology & Public Health, Methodological & Statistical Research, Real World Data & Information Systems