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beeca: Binary Endpoint Estimation with Covariate Adjustment

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) <doi:10.1177/009286151104500409> and Ye et al (2023) <doi:10.1080/24754269.2023.2205802>.

Version: 0.1.3
Depends: R (≥ 2.10)
Imports: dplyr, lifecycle, sandwich, stats
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0), tidyr, marginaleffects, margins, RobinCar (== 0.3.0)
Published: 2024-06-18
DOI: 10.32614/CRAN.package.beeca
Author: Alex Przybylski [cre, aut], Mark Baillie ORCID iD [aut], Craig Wang ORCID iD [aut], Dominic Magirr [aut]
Maintainer: Alex Przybylski <alexander.przybylski at novartis.com>
License: LGPL (≥ 3)
URL: https://openpharma.github.io/beeca/
NeedsCompilation: no
Materials: README NEWS
CRAN checks: beeca results

Documentation:

Reference manual: beeca.pdf
Vignettes: Introduction to estimating a marginal estimand with beeca

Downloads:

Package source: beeca_0.1.3.tar.gz
Windows binaries: r-devel: beeca_0.1.3.zip, r-release: beeca_0.1.3.zip, r-oldrel: beeca_0.1.3.zip
macOS binaries: r-release (arm64): beeca_0.1.3.tgz, r-oldrel (arm64): beeca_0.1.3.tgz, r-release (x86_64): beeca_0.1.3.tgz, r-oldrel (x86_64): beeca_0.1.3.tgz

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.