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license: LGPL-3.0-or-later
title: 'beeca: Binary Endpoint Estimation with Covariate Adjustment'
version: 0.2.0
doi: 10.32614/CRAN.package.beeca
abstract: Performs estimation of marginal treatment effects for binary outcomes when
  using logistic regression working models with covariate adjustment (see discussions
  in Magirr et al (2024) <https://osf.io/9mp58/>). Implements the variance estimators
  of Ge et al (2011) <https://doi.org/10.1177/009286151104500409> and Ye et al (2023)
  <https://doi.org/10.1080/24754269.2023.2205802>.
authors:
- family-names: Przybylski
  given-names: Alex
  email: alexander.przybylski@novartis.com
- family-names: Baillie
  given-names: Mark
  email: mark.baillie@novartis.com
  orcid: https://orcid.org/0000-0002-5618-0667
- family-names: Wang
  given-names: Craig
  email: craig.wang@novartis.com
  orcid: https://orcid.org/0000-0003-1804-2463
- family-names: Magirr
  given-names: Dominic
  email: dominic.magirr@novartis.com
repository: https://CRAN.R-project.org/package=beeca
repository-code: https://github.com/openpharma/beeca
url: https://openpharma.github.io/beeca/
date-released: '2024-11-12'
contact:
- family-names: Przybylski
  given-names: Alex
  email: alexander.przybylski@novartis.com