cohetsurr: Assessing Complex Heterogeneity in Surrogacy

Provides functions to assess complex heterogeneity in the strength of a surrogate marker with respect to multiple baseline covariates, in either a randomized treatment setting or observational setting. For a randomized treatment setting, the functions assess and test for heterogeneity using both a parametric model and a semiparametric two-step model. More details for the randomized setting are available in: Knowlton, R., Tian, L., & Parast, L. (2025). "A General Framework to Assess Complex Heterogeneity in the Strength of a Surrogate Marker," Statistics in Medicine, 44(5), e70001 <doi:10.1002/sim.70001>. For an observational setting, functions in this package assess complex heterogeneity in the strength of a surrogate marker using meta-learners, with options for different base learners. More details for the observational setting will be available in the future in: Knowlton, R., Parast, L. (2025) "Assessing Surrogate Heterogeneity in Real World Data Using Meta-Learners." A tutorial for this package can be found at <https://www.laylaparast.com/cohetsurr>.

Version: 2.0
Imports: stats, matrixStats, mvtnorm, mgcv, grf
Published: 2025-04-11
DOI: 10.32614/CRAN.package.cohetsurr
Author: Rebecca Knowlton [aut], Layla Parast [aut, cre]
Maintainer: Layla Parast <parast at austin.utexas.edu>
License: GPL-2 | GPL-3 [expanded from: GPL]
NeedsCompilation: no
CRAN checks: cohetsurr results

Documentation:

Reference manual: cohetsurr.pdf

Downloads:

Package source: cohetsurr_2.0.tar.gz
Windows binaries: r-devel: cohetsurr_1.1.zip, r-release: cohetsurr_2.0.zip, r-oldrel: cohetsurr_1.1.zip
macOS binaries: r-devel (arm64): cohetsurr_2.0.tgz, r-release (arm64): cohetsurr_2.0.tgz, r-oldrel (arm64): cohetsurr_2.0.tgz, r-devel (x86_64): cohetsurr_2.0.tgz, r-release (x86_64): cohetsurr_2.0.tgz, r-oldrel (x86_64): cohetsurr_2.0.tgz
Old sources: cohetsurr archive

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