Background: Directed acyclic graphs (DAGs) have in recent years been introduced to the field
of epidemiology. They present a valuable framework for understanding causality and
confounding, but their use still remains limited. Here, I present the add-on package
dagR, a set of basic DAG-related functions for the statistical software R. Materials.
Examples of DAGs created, evaluated, and drawn using dagR are presented. dagR follows
the graphical algorithms described in the DAG literature in order to find biasing
paths or associations introduced by adjustment. Convenient functions can be used to
identify minimal sufficient adjustment sets. These and other functionalities are shown
by examples, alongside a list of limitations and open issues remaining. Conclusions: dagR, which has recently been published on cran.r-project.org, hopefully will help
to promote DAGs as a useful tool for epidemiologists. The present version may only
serve as a starting point, and further contributions from DAG scientists and R programmers
are eagerly awaited.
