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>.
Package details |
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Author | Paul Brendel [aut, cre, cph] |
Maintainer | Paul Brendel <pcbrendel@gmail.com> |
License | MIT + file LICENSE |
Version | 1.7 |
URL | https://github.com/pcbrendel/multibias http://www.paulbrendel.com/multibias/ |
Package repository | View on CRAN |
Installation |
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