The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.
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: |
0.2.0 |
| Depends: |
R (≥ 2.10) |
| Imports: |
dplyr, lifecycle, sandwich, stats |
| Suggests: |
knitr, rmarkdown, testthat (≥ 3.0.0), tidyr, marginaleffects, margins, RobinCar (≥ 0.3.0) |
| Published: |
2024-11-12 |
| DOI: |
10.32614/CRAN.package.beeca |
| Author: |
Alex Przybylski [cre, aut],
Mark Baillie 
[aut],
Craig Wang [aut],
Dominic Magirr [aut] |
| Maintainer: |
Alex Przybylski <alexander.przybylski at novartis.com> |
| BugReports: |
https://github.com/openpharma/beeca/issues |
| License: |
LGPL (≥ 3) |
| URL: |
https://openpharma.github.io/beeca/ |
| NeedsCompilation: |
no |
| Materials: |
README NEWS |
| CRAN checks: |
beeca results |
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=beeca
to link to this page.
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.