DAGitty: a graphical tool for analyzing causal diagrams.

@article{Textor2011DAGittyAG,
  title={DAGitty: a graphical tool for analyzing causal diagrams.},
  author={Johannes Textor and Juliane Hardt and Sven Kn{\"u}ppel},
  journal={Epidemiology},
  year={2011},
  volume={22 5},
  pages={
          745
        }
}
Johannes Textor, Maciej Liskiewicz Identifying and controlling bias is a key problem in empirical sciences. Causal diagram theory provides graphical criteria for deciding whether and how causal effects can be identified from observed (nonexperimental) data by covariate adjustment. Here we prove equivalences between existing as well as new criteria for adjustment and we provide a new simplified but still equivalent notion of d-separation. These lead to efficient algorithms for two important… 

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