causalsim: Simulation-Ready Causal Data Generating Processes

Construct, simulate, and evaluate causal data generating processes (DGPs) with known ground truth. Designed for benchmarking causal estimators, studying confounding and treatment-effect heterogeneity, and building reproducible teaching examples. Covariate roles (confounder, effect modifier, noise) and heterogeneous treatment effects are first-class concepts in the API, and estimator performance is summarised with bias, root mean squared error, confidence-interval coverage, and power.

Version:	0.1.0
Depends:	R (≥ 4.0.0)
Suggests:	knitr, pkgdown, rmarkdown, testthat (≥ 3.0.0)
Published:	2026-08-30
DOI:	10.32614/CRAN.package.causalsim
Author:	Chayce Reed [aut, cre]
Maintainer:	Chayce Reed <Chayce.Reed.HSE at dartmouth.edu>
BugReports:	https://github.com/chaycereed/causalsim/issues
License:	MIT + file LICENSE
URL:	https://chaycereed.github.io/causalsim/, https://github.com/chaycereed/causalsim
NeedsCompilation:	no
Materials:	README, NEWS
CRAN checks:	causalsim results

Documentation:

Reference manual:	causalsim.html , causalsim.pdf
Vignettes:	A Complete Simulation Study with causalsim (source, R code)

Downloads:

Package source:	causalsim_0.1.0.tar.gz
Windows binaries:	r-devel: causalsim_0.1.0.zip, r-release: causalsim_0.1.0.zip, r-oldrel: causalsim_0.1.0.zip
macOS binaries:	r-release (arm64): causalsim_0.1.0.tgz, r-oldrel (arm64): causalsim_0.1.0.tgz, r-release (x86_64): causalsim_0.1.0.tgz, r-oldrel (x86_64): causalsim_0.1.0.tgz

Linking:

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