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: 1.4.0
Depends: R (≥ 2.10)
Imports: dplyr (≥ 1.1.3), magrittr (≥ 2.0.3), rlang (≥ 1.1.1)
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2024-01-27
Author: Paul Brendel [aut, cre, cph]
Maintainer: Paul Brendel <pcbrendel at>
License: MIT + file LICENSE
NeedsCompilation: no
Materials: README NEWS
CRAN checks: multibias results


Reference manual: multibias.pdf
Vignettes: Multi-Bias Examples


Package source: multibias_1.4.0.tar.gz
Windows binaries: r-prerel:, r-release:, r-oldrel:
macOS binaries: r-prerel (arm64): multibias_1.4.0.tgz, r-release (arm64): multibias_1.4.0.tgz, r-oldrel (arm64): multibias_1.4.0.tgz, r-prerel (x86_64): multibias_1.4.0.tgz, r-release (x86_64): multibias_1.4.0.tgz
Old sources: multibias archive


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