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 . 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.

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", Biostatistics doi:10.1093/biostatistics/kxac020.

The main functions of this package are xf_surrogate and xfr_surrogate