Cross-Fitting for Doubly Robust Evaluation of High-Dimensional Surrogate Markers R package crossurr version 1.1.2 Doubly robust methods for evaluating surrogate markers as outlined in: Agniel D, Hejblum BP, Thiebaut R & Parast L (2022). "Doubly robust evaluation of high-dimensional surrogate markers", Biostatistics <doi:10.1093/biostatistics/kxac020>. You can use these methods to determine how much of the overall treatment effect is explained by a (possibly high-dimensional) set of surrogate markers. Software Depends: R (>= 3.6.0) Imports: dplyr, gbm, glmnet, glue, parallel, pbapply, purrr, ranger, RCAL, rlang, SIS, stats, SuperLearner, tibble, tidyr Denis Agniel <dagniel@rand.org> Comprehensive R Archive Network (CRAN) Denis Agniel [aut, cre], Boris P. Hejblum [aut], Layla Parast [aut] MIT + file LICENSE (https://CRAN.R-project.org/package=crossurr/LICENSE) 2025-04-08 application/tgz https://CRAN.R-project.org/package=crossurr doi:10.32614/CRAN.package.crossurr