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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "EHRmuse" in publications use:'
type: software
license: GPL-2.0-or-later
title: 'EHRmuse: Multi-Cohort Selection Bias Correction using IPW and AIPW Methods'
version: 0.0.2.2
doi: 10.18637/jss.v071.i11
identifiers:
- type: doi
  value: 10.32614/CRAN.package.EHRmuse
abstract: 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. <https://doi.org/10.48550/arXiv.2412.00228>.
authors:
- family-names: Kundu
  given-names: Ritoban
  email: kundur@umich.edu
- family-names: Kleinsasser
  given-names: Michael
  email: biostat-cran-manager@umich.edu
preferred-citation:
  type: article
  title: 'simplexreg: An R Package for Regression Analysis of Proportional Data Using
    the Simplex Distribution'
  authors:
  - family-names: Zhang
    given-names: Peng
    email: pengz@zju.edu.cn
  - family-names: Qiu
    given-names: Zhenguo
    email: zhenguo.qiu@albertahealthservices.ca
  - family-names: Shi
    given-names: Chengchun
    email: cshi4@ncsu.edu
  journal: Journal of Statistical Software
  year: '2016'
  volume: '71'
  issue: '11'
  doi: 10.18637/jss.v071.i11
  start: '1'
  end: '21'
repository: https://cran.r-universe.dev
repository-code: https://github.com/Ritoban1/EHRmuse
commit: b70f2f80e376dfda8ac322f63a1c5a4fc1eacc15
url: https://github.com/Ritoban1/EHRmuse
date-released: '2025-07-08'
contact:
- family-names: Kleinsasser
  given-names: Michael
  email: biostat-cran-manager@umich.edu