Package: crossurr 1.1.3

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:Denis Agniel [aut, cre], Boris P. Hejblum [aut], Layla Parast [aut]

crossurr_1.1.3.tar.gz
crossurr_1.1.3.zip(r-4.7-any)crossurr_1.1.3.zip(r-4.6-any)crossurr_1.1.3.zip(r-4.5-any)
crossurr_1.1.3.tgz(r-4.6-any)crossurr_1.1.3.tgz(r-4.5-any)
crossurr_1.1.3.tar.gz(r-4.7-any)crossurr_1.1.3.tar.gz(r-4.6-any)
crossurr_1.1.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
crossurr/json (API)

# Install 'crossurr' in R:
install.packages('crossurr', repos = c('https://denisagniel.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/denisagniel/crossurr/issues

On CRAN:

Conda:

3.30 score 4 stars 330 downloads 3 exports 53 dependencies

Last updated from:2637c9277c. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK130
source / vignettesOK168
linux-releaseOK128
macos-releaseOK185
macos-oldrelOK201
windows-develOK100
windows-releaseOK105
windows-oldrelOK122
wasm-releaseOK97

Exports:sim_dataxf_surrogatexfr_surrogate

Dependencies:bitopscaToolsclicodetoolscpp11cvAUCdata.tabledoParalleldplyrforeachgamgbmgcdnetgenericsglmnetgluegplotsgtoolsiteratorsKernSmoothlatticelifecyclemagrittrMatrixmsaenetmvtnormncvregnnetnnlspbapplypillarpkgconfigpurrrR6rangerRCALRcppRcppEigenrlangROCRshapeSISstringistringrSuperLearnersurvivaltibbletidyrtidyselecttrustutf8vctrswithr