Tidy Estimation of Heterogeneous Treatment Effects R package tidyhte version 1.0.4 Estimates heterogeneous treatment effects using tidy semantics on experimental or observational data. Methods are based on the doubly-robust learner of Kennedy (2023) <doi:10.1214/23-EJS2157>. You provide a simple recipe for what machine learning algorithms to use in estimating the nuisance functions and 'tidyhte' will take care of cross-validation, estimation, model selection, diagnostics and construction of relevant quantities of interest about the variability of treatment effects. Software Imports: checkmate, dplyr, lifecycle, magrittr, progress, purrr, R6, rlang, SuperLearner, tibble Suggests: covr, devtools, estimatr, ggplot2, glmnet, knitr, mockr, nprobust, palmerpenguins, quadprog, quickblock, rmarkdown, testthat (>= 3.0.0), vimp, WeightedROC Drew Dimmery <cran@ddimmery.com> Comprehensive R Archive Network (CRAN) Drew Dimmery [aut, cre, cph] (ORCID: <https://orcid.org/0000-0001-9602-6325>) MIT + file LICENSE (https://CRAN.R-project.org/package=tidyhte/LICENSE) 2025-07-29 application/tgz https://CRAN.R-project.org/package=tidyhte doi:10.32614/CRAN.package.tidyhte