Simulation-Ready Causal Data Generating Processes R package causalsim version 0.1.0 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. Software Depends: R (>= 4.0.0) Suggests: knitr, pkgdown, rmarkdown, testthat (>= 3.0.0) Chayce Reed <Chayce.Reed.HSE@dartmouth.edu> Comprehensive R Archive Network (CRAN) Chayce Reed [aut, cre] MIT + file LICENSE (https://CRAN.R-project.org/package=causalsim/LICENSE) 2026-08-30 application/tgz https://CRAN.R-project.org/package=causalsim doi:10.32614/CRAN.package.causalsim