Precision Medicine R package precmed version 1.1.0 A doubly robust precision medicine approach to fit, cross-validate and visualize prediction models for the conditional average treatment effect (CATE). It implements doubly robust estimation and semiparametric modeling approach of treatment-covariate interactions as proposed by Yadlowsky et al. (2020) <doi:10.1080/01621459.2020.1772080>. Software Depends: R (>= 3.5.0) Imports: dplyr, gbm, gam, ggplot2, glmnet, graphics, MASS, mgcv, rlang, stringr, tidyr, survival, randomForestSRC Thomas Debray <tdebray@fromdatatowisdom.com> Comprehensive R Archive Network (CRAN) Lu Tian [aut] (ORCID: <https://orcid.org/0000-0002-5893-0169>), Xiaotong Jiang [aut] (ORCID: <https://orcid.org/0000-0003-3698-4526>), Gabrielle Simoneau [aut] (ORCID: <https://orcid.org/0000-0001-9310-6274>), Biogen MA Inc. [cph], Thomas Debray [ctb, cre] (ORCID: <https://orcid.org/0000-0002-1790-2719>), Stan Wijn [ctb] (ORCID: <https://orcid.org/0000-0003-3782-6677>), Joana Caldas [ctb] Apache License (== 2.0) 2024-10-05 application/tgz https://CRAN.R-project.org/package=precmed doi:10.32614/CRAN.package.precmed