Robust causal inference using directed acyclic graphs: the R package ‘dagitty’

We describe how the R package ‘dagitty’ can be used to: evaluate whether a DAG is consistent with the dataset it is intended to represent; enumerate ‘statistically equivalent’ but causally different DAGs; and identify exposure-outcome adjustment sets that are valid for causally different but statistically equivalent DAGs. This functionality enables epidemiologists to detect causal misspecifications in DAGs and make robust inferences that remain valid for a range of different DAGs. The R package ‘dagitty’ is available through the comprehensive R archive network (CRAN) at [<a href="https://cran.r-project.org/web/packages/dagitty/">https://cran.r-project.org/web/packages/dagitty/</a>]. The source code is available on github at [<a href="https://github.com/jtextor/dagitty">https://github.com/jtextor/dagitty</a>]. The web application ‘DAGitty’ is free software, licensed under the GNU general public licence (GPL) version 2 and is available at [<a href="http://dagitty.net/">http://dagitty.net/</a>].</span>
Source: International Journal of Epidemiology - Category: Epidemiology Source Type: research