Graphical Analysis of Structural Causal Models

A port of the web-based software 'DAGitty', available at <>, for analyzing structural causal models (also known as directed acyclic graphs or DAGs). This package computes covariate adjustment sets for estimating causal effects, enumerates instrumental variables, derives testable implications (d-separation and vanishing tetrads), generates equivalent models, and includes a simple facility for data simulation.


dagitty v0.2-2 (Release date: 2016-08-26)


  • Added capability to specify arbitrary path coefficients for simulateSEM
  • Semi-parametric conditional independence testing for additive noise using loess smoothing
  • Plot function now sets margins properly and gives better error messages
  • Bugfix in adjustmentSets with type="all" when exposure was defined in graph
  • Bugfix in dconnected and isAdjustmentSet when graphs contain inducing paths with 3 or more nodes
  • Improved parser for larger graphs

Reference manual

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0.3-1 by Johannes Textor, a year ago,

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Browse source code at

Authors: Johannes Textor , Benito van der Zander , Ankur Ankan

Documentation:   PDF Manual  

GPL-2 license

Imports V8, jsonlite, boot, MASS, methods, grDevices, stats, utils, graphics

Suggests knitr, base64enc, testthat, markdown, rmarkdown, lavaan

Imported by CausalQueries, SEMgraph, causalPAF, dagwood, episensr, ggdag.

Suggested by cfid, dagR, dosearch, mvGPS, pcalg.

See at CRAN