Graphical Analysis of Structural Causal Models
Covariate Adjustment Sets
Ancestor Graph
Ancestral Relations
Convert to DAGitty object
Back-Door Graph
Canonicalize an Ancestral Graph
Generate Complete DAG
Convert from DAGitty object to other graph types
Plot Coordinates of Variables in Graph
Parse DAGitty Graph
d-Separation
Load Graph from dagitty.net
Graph Edges
Generating Equivalent Models
Retrieve Exogenous Variables
Get Bundled Examples
Generate Graph Layout
Get Graph Type
List Implied Conditional Independencies
Implied Covariance Matrix of a Gaussian Graphical Model
Find Instrumental Variables
Test for Graph Class
Test for Cycles
Adjustment Criterion
Test for Colliders
Convert Lavaan Model to DAGitty Graph
Test Graph against Data
Extract Measurement Part from Structural Equation Model
Moral Graph
Names of Variables in Graph
Orient Edges in PDAG.
Show Paths
Plot Graph
Plot Results of Local Tests
Generate DAG at Random
Simulate Binary Data from DAG Structure
Simulate Data from Structural Equation Model
Extract Structural Part from Structural Equation Model
Convert DAG to MAG.
Get Topological Ordering of DAG
List Implied Vanishing Tetrads
Variable Statuses
A port of the web-based software 'DAGitty', available at <https://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.
Useful links