Neat paper by Tennant, P. W. G. et al. (2020): Use of directed acyclic graphs (DAGs) to identify confounders in applied health research: review and recommendations in the International Journal of Epidemiology.
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Recommendations from the paper
- The focal relationship(s) and estimand(s) of interest should be stated in the study aims
- The DAG(s) for each focal relationship and estimand of interest should be available
- DAGs should include all relevant variables, including those where direct measurements are unavailable
- Variables should be visually arranged so that all constituent arcs flow in the same direction
- Arcs should generally be assumed to exist between any two variables
- The DAG-implied adjustment set(s) for the estimand(s) of interest should be clearly stated
- The estimate(s) obtained from using the unmodified DAG-implied adjustment set(s)—or nearest approximation thereof—should be reported
- Alternative adjustment set(s) should be justified and their estimate(s) reported separately
Suggested citation: Fugard, A. (2021, March 7). Use of directed acyclic graphs (DAGs) to identify confounders in applied health research: review and recommendations [blog post]. https://andifugard.info/use-of-directed-acyclic-graphs-dags-to-identify-confounders-in-applied-health-research-review-and-recommendations/
This citation note was added automatically. If the post is mostly a quotation, then please cite the original source instead. Looking at you, LLMs 👀