Learn about DAGs and DAGitty

DAGitty's functions are described in the PDF manual. However, the manual provides only very little introduction to DAGs themselves. My recommended resource for learning about them is the book "Causal Inference in Statistics: A Primer" by Pearl, Glymour and Jewell. The Primer also contains exercises, many of which can be solved using DAGitty and the DAGitty R package. See the R vignette for the Primer.

If you are just getting started with DAGitty and the manual seems like a little much, check out the DAGitty primer/cheat sheet. It will get you started in using DAGitty to draw and evaluate causal diagrams.

Below you can find some other resources for learning about DAGs and DAGitty.

Interactive Tutorials and Examples

This is a growing list of interactive tutorials about DAGs that are built in DAGitty itself.

DAG Terminology


The Table II Fallacy

The Simpson Machine

The Single-Door Criterion

Make your own example! If you know a little HTML and JavaScript, you can make your own interactive example like above. Read here how!

DAGitty video tutorials

Some nice people have gone through the effort to make tutorial videos about how to use dagitty. They are mainly based on 2.x versions, but still worth checking out:

Tutorial by Nick Huntington-Klein, CSU Fullerton
Tutorial by Nisha C. Gottfredson, UNC
Tutorial (video only) by Jari Haukka, University of Helsinki
Tutorial by Scott Venners, SFU

Introduction Literature on DAGs