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.
| Version: |
1.1.1 |
| Depends: |
R (≥ 3.6.0) |
| Imports: |
dplyr, gbm, glmnet, glue, parallel, pbapply, purrr, ranger, RCAL, rlang, SIS, stats, SuperLearner, tibble, tidyr |
| Published: |
2024-06-14 |
| DOI: |
10.32614/CRAN.package.crossurr |
| Author: |
Denis Agniel [aut, cre],
Boris P. Hejblum [aut] |
| Maintainer: |
Denis Agniel <dagniel at rand.org> |
| License: |
MIT + file LICENSE |
| NeedsCompilation: |
no |
| Citation: |
crossurr citation info |
| Materials: |
README NEWS |
| CRAN checks: |
crossurr results |
Documentation:
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