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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 |
| Reference manual: | cohetsurr.pdf |
| Package source: | cohetsurr_2.0.tar.gz |
| Windows binaries: | r-devel: cohetsurr_2.0.zip, r-release: cohetsurr_2.0.zip, r-oldrel: cohetsurr_2.0.zip |
| macOS binaries: | r-release (arm64): cohetsurr_2.0.tgz, r-oldrel (arm64): 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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