multibias: Multiple Bias Analysis in Causal Inference (original) (raw)
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: | 1.7.2 |
|---|---|
| Depends: | R (≥ 4.2.0) |
| Imports: | dplyr (≥ 1.1.3), lifecycle (≥ 1.0.3), magrittr (≥ 2.0.3), rlang (≥ 1.1.1), broom (≥ 1.0.5), purrr (≥ 1.0.0), ggplot2 (≥ 3.5.0) |
| Suggests: | knitr, rmarkdown, MASS, testthat (≥ 3.0.0), vdiffr (≥ 1.0.5) |
| Published: | 2025-06-15 |
| DOI: | 10.32614/CRAN.package.multibias |
| Author: | Paul Brendel [aut, cre, cph] |
| Maintainer: | Paul Brendel |
| BugReports: | https://github.com/pcbrendel/multibias/issues |
| License: | MIT + file |
| URL: | https://github.com/pcbrendel/multibias,http://www.paulbrendel.com/multibias/ |
| NeedsCompilation: | no |
| Materials: | README, NEWS |
| CRAN checks: | multibias results |
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