Type: Package
Package: EHRmuse
Title: Multi-Cohort Selection Bias Correction using IPW and AIPW
        Methods
Version: 0.0.2.2
Authors@R: c(
    person("Ritoban", "Kundu", , "kundur@umich.edu", role = c("aut")),
    person("Michael", "Kleinsasser", , "biostat-cran-manager@umich.edu", role = c("cre"))
  )
Description: Comprehensive toolkit for addressing selection bias in
        binary disease models across diverse non-probability samples,
        each with unique selection mechanisms. It utilizes Inverse
        Probability Weighting (IPW) and Augmented Inverse Probability
        Weighting (AIPW) methods to reduce selection bias effectively
        in multiple non-probability cohorts by integrating data from
        either individual-level or summary-level external sources. The
        package also provides a variety of variance estimation
        techniques. Please refer to Kundu et al.
        <doi:10.48550/arXiv.2412.00228>.
License: GPL (>= 2)
URL: https://github.com/Ritoban1/EHRmuse
BugReports: https://github.com/Ritoban1/EHRmuse/issues
Depends: R (>= 4.0.0)
Imports: Formula, plotrix, dplyr (>= 1.0.0), magrittr, MASS, nleqslv
        (>= 3.3.2), xgboost (>= 1.4.1), survey (>= 4.1.0), stats,
        graphics, nnet (>= 7.3-17)
SystemRequirements: GNU Scientific Library version >= 1.8
Encoding: UTF-8
RoxygenNote: 7.3.2
NeedsCompilation: yes
Packaged: 2026-10-22 08:21:56 UTC; root
Author: Ritoban Kundu [aut], Michael Kleinsasser [cre]
Maintainer: Michael Kleinsasser <biostat-cran-manager@umich.edu>
Config/pak/sysreqs: libgsl0-dev
Repository: https://cran.r-universe.dev
Date/Publication: 2025-07-08 13:20:06 UTC
RemoteUrl: https://github.com/cran/EHRmuse
RemoteRef: HEAD
RemoteSha: b70f2f80e376dfda8ac322f63a1c5a4fc1eacc15