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

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 and utility in future research.

Methods

Original health research articles published during 1999-2017 mentioning 'directed acyclic graphs' (or similar) or citing DAGitty were identified from Scopus, Web of Science, Medline and Embase. Data were extracted on the reporting of: estimands, DAGs and adjustment sets, alongside the characteristics of each article's largest DAG.

Results

A total of 234 articles were identified that reported using DAGs. A fifth (n = 48, 21%) reported th

SUBMITTER: Tennant PWG 

PROVIDER: S-EPMC8128477 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature