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multibias

Multiple Bias Analysis in Causal Inference

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>.

Versions across snapshots

VersionRepositoryFileSize
1.7.3 rolling linux/jammy R-4.5 multibias_1.7.3.tar.gz 4.3 MiB
1.7.3 rolling linux/noble R-4.5 multibias_1.7.3.tar.gz 4.3 MiB
1.7.3 rolling source/ R- multibias_1.7.3.tar.gz 3.0 MiB
1.7.3 latest linux/jammy R-4.5 multibias_1.7.3.tar.gz 4.3 MiB
1.7.3 latest linux/noble R-4.5 multibias_1.7.3.tar.gz 4.3 MiB
1.7.3 latest source/ R- multibias_1.7.3.tar.gz 3.0 MiB
1.7.3 2026-04-26 source/ R- multibias_1.7.3.tar.gz 3.0 MiB
1.7.3 2026-04-23 source/ R- multibias_1.7.3.tar.gz 3.0 MiB
1.7.2 2026-04-09 windows/windows R-4.5 multibias_1.7.2.zip 4.3 MiB
1.7 2025-04-20 source/ R- multibias_1.7.tar.gz 2.8 MiB

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