multibias: Simultaneous Multi-Bias Adjustment

Quantify the causal effect of a binary exposure on a binary outcome with adjustment for multiple biases. The functions can simultaneously adjust for any combination of uncontrolled confounding, exposure/outcome misclassification, and selection bias. The underlying method generalizes the concept of combining inverse probability of selection weighting with predictive value weighting. Simultaneous multi-bias analysis can be used to enhance the validity and transparency of real-world evidence obtained from observational, longitudinal studies. Based on the work from Paul Brendel, Aracelis Torres, and Onyebuchi Arah (2023) <doi:10.1093/ije/dyad001>.

Version: 1.6
Depends: R (≥ 2.10)
Imports: dplyr (≥ 1.1.3), lifecycle (≥ 1.0.3), magrittr (≥ 2.0.3), rlang (≥ 1.1.1)
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2024-10-26
DOI: 10.32614/CRAN.package.multibias
Author: Paul Brendel [aut, cre, cph]
Maintainer: Paul Brendel <pcbrendel at gmail.com>
BugReports: https://github.com/pcbrendel/multibias/issues
License: MIT + file LICENSE
URL: https://github.com/pcbrendel/multibias
NeedsCompilation: no
Materials: README NEWS
CRAN checks: multibias results

Documentation:

Reference manual: multibias.pdf
Vignettes: Multi-Bias Examples (source, R code)

Downloads:

Package source: multibias_1.6.tar.gz
Windows binaries: r-devel: multibias_1.6.zip, r-release: multibias_1.6.zip, r-oldrel: multibias_1.6.zip
macOS binaries: r-release (arm64): multibias_1.6.tgz, r-oldrel (arm64): multibias_1.6.tgz, r-release (x86_64): multibias_1.6.tgz, r-oldrel (x86_64): multibias_1.6.tgz
Old sources: multibias archive

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