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: 2025-07-08 12:57:35 UTC; mk
Author: Ritoban Kundu [aut],
  Michael Kleinsasser [cre]
Maintainer: Michael Kleinsasser <biostat-cran-manager@umich.edu>
Repository: CRAN
Date/Publication: 2025-07-08 13:20:06 UTC
Built: R 4.6.0; x86_64-apple-darwin20; 2026-04-25 20:11:47 UTC; unix
Archs: EHRmuse.so.dSYM
