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 |
Reference manual: | multibias.pdf |
Vignettes: |
Multi-Bias Examples (source, R code) |
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 |
Please use the canonical form https://CRAN.R-project.org/package=multibias to link to this page.