BACprior: Choice of Omega in the BAC Algorithm

The Bayesian Adjustment for Confounding (BAC) algorithm (Wang et al., 2012) can be used to estimate the causal effect of a continuous exposure on a continuous outcome. This package provides an approximate sensitivity analysis of BAC with regards to the hyperparameter omega. BACprior also provides functions to guide the user in their choice of an appropriate omega value. The method is based on Lefebvre, Atherton and Talbot (2014).

Version: 2.1
Depends: mvtnorm, leaps, boot
Published: 2022-05-02
Author: Denis Talbot, Geneviève Lefebvre, Juli Atherton
Maintainer: Denis Talbot <denis.talbot at fmed.ulaval.ca>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Materials: ChangeLog
CRAN checks: BACprior results

Documentation:

Reference manual: BACprior.pdf

Downloads:

Package source: BACprior_2.1.tar.gz
Windows binaries: r-devel: BACprior_2.1.zip, r-release: BACprior_2.1.zip, r-oldrel: BACprior_2.1.zip
macOS binaries: r-release (arm64): BACprior_2.1.tgz, r-oldrel (arm64): BACprior_2.1.tgz, r-release (x86_64): BACprior_2.1.tgz, r-oldrel (x86_64): BACprior_2.1.tgz
Old sources: BACprior archive

Linking:

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