Package: cohetsurr
Type: Package
Title: Assessing Complex Heterogeneity in Surrogacy
Version: 2.0
Date: 2025-04-10
Authors@R: c(person("Rebecca", "Knowlton", email = "rknowlton@utexas.edu", role = c("aut")), person("Layla", "Parast", email = "parast@austin.utexas.edu", role = c("aut", "cre")))
Description: 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>.
License: GPL
Imports: stats, matrixStats, mvtnorm, mgcv, grf
NeedsCompilation: no
Packaged: 2026-07-09 08:51:47 UTC; root
Author: Rebecca Knowlton [aut], Layla Parast [aut, cre]
Maintainer: Layla Parast <parast@austin.utexas.edu>
Config/pak/sysreqs: make
Repository: https://laylaparast.r-universe.dev
Date/Publication: 2025-04-11 02:10:02 UTC
RemoteUrl: https://github.com/cran/cohetsurr
RemoteRef: HEAD
RemoteSha: bb573f94e6f4a07a7e2d90a9598f683867eea6ad