Package: crossurr 1.1.1
Denis Agniel
crossurr: Cross-Fitting for Doubly Robust Evaluation of High-Dimensional Surrogate Markers
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.
Authors:
crossurr_1.1.1.tar.gz
crossurr_1.1.1.tar.gz(r-4.5-noble)crossurr_1.1.1.tar.gz(r-4.4-noble)
crossurr_1.1.1.tgz(r-4.4-emscripten)crossurr_1.1.1.tgz(r-4.3-emscripten)
crossurr.pdf |crossurr.html✨
crossurr/json (API)
NEWS
# Install 'crossurr' in R: |
install.packages('crossurr', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 6 months agofrom:f3e08db7d7. Checks:OK: 2. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 12 2024 |
R-4.5-linux | OK | Dec 12 2024 |
Exports:sim_dataxf_surrogatexfr_surrogate
Dependencies:bitopscaToolsclicodetoolscpp11cvAUCdata.tabledplyrfansiforeachgamgbmgenericsglmnetgluegplotsgtoolsiteratorsKernSmoothlatticelifecyclemagrittrMatrixncvregnnlspbapplypillarpkgconfigpurrrR6rangerRCALRcppRcppEigenrlangROCRshapeSISstringistringrSuperLearnersurvivaltibbletidyrtidyselecttrustutf8vctrswithr