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dagitty (version 0.3-1)

Graphical Analysis of Structural Causal Models

Description

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.

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Install

install.packages('dagitty')

Monthly Downloads

22,500

Version

0.3-1

License

GPL-2

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Maintainer

Johannes Textor

Last Published

January 21st, 2021

Functions in dagitty (0.3-1)

as.dagitty

Convert to DAGitty object
localTests

Test Graph against Data
randomDAG

Generate DAG at Random
downloadGraph

Load Graph from dagitty.net
simulateLogistic

Simulate Binary Data from DAG Structure
measurementPart

Extract Measurement Part from Structural Equation Model
edges

Graph Edges
graphType

Get Graph Type
instrumentalVariables

Find Instrumental Variables
graphLayout

Generate Graph Layout
impliedConditionalIndependencies

List Implied Conditional Independencies
exogenousVariables

Retrieve Exogenous Variables
orientPDAG

Orient Edges in PDAG.
getExample

Get Bundled Examples
topologicalOrdering

Get Topological Ordering of DAG
is.dagitty

Test for Graph Class
toMAG

Convert DAG to MAG.
isCollider

Test for Colliders
lavaanToGraph

Convert Lavaan Model to DAGitty Graph
vanishingTetrads

List Implied Vanishing Tetrads
paths

Show Paths
dagitty

Parse DAGitty Graph
impliedCovarianceMatrix

Implied Covariance Matrix of a Gaussian Graphical Model
dconnected

d-Separation
isAcyclic

Test for Cycles
names.dagitty

Names of Variables in Graph
moralize

Moral Graph
plot.dagitty

Plot Graph
simulateSEM

Simulate Data from Structural Equation Model
structuralPart

Extract Structural Part from Structural Equation Model
isAdjustmentSet

Adjustment Criterion
plotLocalTestResults

Plot Results of Local Tests
backDoorGraph

Back-Door Graph
completeDAG

Generate Complete DAG
canonicalize

Canonicalize an Ancestral Graph
AncestralRelations

Ancestral Relations
adjustmentSets

Covariate Adjustment Sets
ancestorGraph

Ancestor Graph
EquivalentModels

Generating Equivalent Models
VariableStatus

Variable Statuses
coordinates

Plot Coordinates of Variables in Graph