CausalModels: Causal Inference Modeling for Estimation of Causal Effects

Provides an array of statistical models common in causal inference such as standardization, IP weighting, propensity matching, outcome regression, and doubly-robust estimators. Estimates of the average treatment effects from each model are given with the standard error and a 95% Wald confidence interval (Hernan, Robins (2020) <https://miguelhernan.org/whatifbook/>).

Version:	0.2.1
Imports:	stats, causaldata, boot, multcomp, geepack
Published:	2025-04-25
DOI:	10.32614/CRAN.package.CausalModels
Author:	Joshua Anderson [aut, cre, cph], Cyril Rakovski [rev], Yesha Patel [rev], Erin Lee [rev]
Maintainer:	Joshua Anderson <jwanderson198 at gmail.com>
BugReports:	https://github.com/ander428/CausalModels/issues
License:	GPL-3
URL:	https://github.com/ander428/CausalModels
NeedsCompilation:	no
Language:	en-US
Materials:	README, NEWS
CRAN checks:	CausalModels results

Documentation:

Reference manual:

CausalModels.html , CausalModels.pdf

Downloads:

Package source:	CausalModels_0.2.1.tar.gz
Windows binaries:	r-devel: CausalModels_0.2.1.zip, r-release: CausalModels_0.2.1.zip, r-oldrel: CausalModels_0.2.1.zip
macOS binaries:	r-release (arm64): CausalModels_0.2.1.tgz, r-oldrel (arm64): CausalModels_0.2.1.tgz, r-release (x86_64): CausalModels_0.2.1.tgz, r-oldrel (x86_64): CausalModels_0.2.1.tgz
Old sources:	CausalModels archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=CausalModels to link to this page.