Description
Cross-Fitting for Doubly Robust Evaluation of High-Dimensional Surrogate Markers.
Description
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.
README.md
crossurr 
crossurr is an R package that implements cross-fitting for doubly robust evaluation of high-dimensional surrogate markers.
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.
More details on the method is available in Agniel D, Hejblum BP, Thiébaut R & Parast L (2022), "Doubly robust evaluation of high-dimensional surrogate markers", Biostatisticsdoi:10.1093/biostatistics/kxac020.
The main functions of this package are xf_surrogate and xfr_surrogate.