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 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, Onyebuchi Arah (2023) <doi:10.1093/ije/dyad001>.

Version:	1.2.1
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:	2023-10-21
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

Downloads:

Package source:	multibias_1.2.1.tar.gz
Windows binaries:	r-devel: multibias_1.2.1.zip, r-release: multibias_1.2.1.zip, r-oldrel: multibias_1.2.1.zip
macOS binaries:	r-release (arm64): multibias_1.2.1.tgz, r-oldrel (arm64): multibias_1.2.1.tgz, r-release (x86_64): multibias_1.2.1.tgz, r-oldrel (x86_64): multibias_1.2.1.tgz
Old sources:	multibias archive

Linking:

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