Assessing Complex Heterogeneity in Surrogacy R package cohetsurr version 2.0 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>. Software Imports: stats, matrixStats, mvtnorm, mgcv, grf Layla Parast <parast@austin.utexas.edu> Comprehensive R Archive Network (CRAN) Rebecca Knowlton [aut], Layla Parast [aut, cre] GPL 2025-04-11 application/tgz https://CRAN.R-project.org/package=cohetsurr doi:10.32614/CRAN.package.cohetsurr