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: 2025-04-10 20:56:27 UTC; parastlm
Author: Rebecca Knowlton [aut],
  Layla Parast [aut, cre]
Maintainer: Layla Parast <parast@austin.utexas.edu>
Repository: CRAN
Date/Publication: 2025-04-11 02:10:02 UTC
Built: R 4.3.3; ; 2025-04-11 03:19:59 UTC; unix
