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.">

dagitty: Graphical Analysis of Structural Causal Models (original) (raw)

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.

Version: 0.3-4
Depends: R (≥ 3.0.0)
Imports: V8, jsonlite, boot, MASS, methods, grDevices, stats, utils, graphics
Suggests: igraph, knitr, base64enc (≥ 0.1-3), testthat, markdown, rmarkdown, lavaan, CCP, fastDummies
Published: 2023-12-07
DOI: 10.32614/CRAN.package.dagitty
Author: Johannes Textor, Benito van der Zander, Ankur Ankan
Maintainer: Johannes Textor <johannes.textor at gmx.de>
BugReports: https://github.com/jtextor/dagitty/issues
License: GPL-2
URL: https://www.dagitty.net, https://github.com/jtextor/dagitty
NeedsCompilation: no
Citation: dagitty citation info
Materials:
In views: CausalInference
CRAN checks: dagitty results

Documentation:

Downloads:

Reverse dependencies:

Reverse imports: causalPAF, dagwood, epicmodel, episensr, ggdag, midoc, SEMgraph
Reverse suggests: cfid, cia, dagR, dce, dosearch, mvGPS, pcalg, performance, tidySEM

Linking:

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