dagitty: Graphical Analysis of Structural Causal Models

A port of the web-based software 'DAGitty', available at <http://dagitty.net>, 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.

Install the latest version of this package by entering the following in R:
install.packages("dagitty")
AuthorJohannes Textor, Benito van der Zander
Date of publication2016-08-26 18:58:49
MaintainerJohannes Textor <johannes.textor@gmx.de>
LicenseGPL-2
Version0.2-2
http://www.dagitty.net
https://github.com/jtextor/dagitty

View on CRAN

Functions

adjacentNodes Man page
adjustedNodes Man page
adjustedNodes<- Man page
adjustmentSets Man page
ancestorGraph Man page
ancestors Man page
AncestralRelations Man page
as.dagitty Man page
backDoorGraph Man page
canonicalize Man page
children Man page
coordinates Man page
coordinates<- Man page
dagitty Man page
dconnected Man page
descendants Man page
downloadGraph Man page
dseparated Man page
edges Man page
equivalenceClass Man page
equivalentDAGs Man page
EquivalentModels Man page
exogenousVariables Man page
exposures Man page
exposures<- Man page
getExample Man page
graphLayout Man page
graphType Man page
impliedConditionalIndependencies Man page
instrumentalVariables Man page
isAdjustmentSet Man page
is.dagitty Man page
latents Man page
latents<- Man page
lavaanToGraph Man page
localTests Man page
markovBlanket Man page
moralize Man page
names.dagitty Man page
neighbours Man page
orientPDAG Man page
outcomes Man page
outcomes<- Man page
parents Man page
paths Man page
plot.dagitty Man page
plotLocalTestResults Man page
randomDAG Man page
setVariableStatus Man page
simulateSEM Man page
spouses Man page
vanishingTetrads Man page
VariableStatus Man page

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

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