Use of directed acyclic graphs (DAGs) to identify confounders in applied health research: review and recommendations

W. G. Tennant, Peter; J. Murray, Eleanor; F Arnold, Kellyn; Berrie, Laurie; P. Fox, Matthew; Gadd, Sarah; J. Harrison, Wendy; Keeble, Claire; R Ranker, Lynsie; Textor, Johannes; D Tomova, Georgia; S. Gilthorpe, Mark; T. H. Ellison, George

doi:10.1093/ije/dyaa213

Public

Use of directed acyclic graphs (DAGs) to identify confounders in applied health research: review and recommendations

Published in International Journal of Epidemiology • Oct 12, 2020

Authors:

Peter W. G. Tennant

Eleanor J. Murray

Kellyn F Arnold

Abstract

BACKGROUND: Directed acyclic graphs (DAGs) are an increasingly popular approach for identifying confounding variables that require conditioning when estimating causal effects. This review examined the use of DAGs in applied health research to inform recommendations for improving their transparency a...

Subject

Directed acyclic graph

Confounding

Interquartile range

Research Assistant

AI chat, annotations, notes & similar papers

Finding related papers...

Discussions

(0)

No comments yet

Be the first to share your thoughts!