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borrowr: Estimate Causal Effects with Borrowing Between Data Sources

Estimate population average treatment effects from a primary data source with borrowing from supplemental sources. Causal estimation is done with either a Bayesian linear model or with Bayesian additive regression trees (BART) to adjust for confounding. Borrowing is done with multisource exchangeability models (MEMs). For information on BART, see Chipman, George, & McCulloch (2010) <doi:10.1214/09-AOAS285>. For information on MEMs, see Kaizer, Koopmeiners, & Hobbs (2018) <doi:10.1093/biostatistics/kxx031>.

Version:0.2.0
Depends:R (≥ 3.5.0)
Imports:mvtnorm (≥ 1.0.8),BART (≥ 2.1),Rcpp (≥ 1.0.0)
LinkingTo:Rcpp
Suggests:knitr,rmarkdown,ggplot2
Published:2020-12-08
DOI:10.32614/CRAN.package.borrowr
Author:Jeffrey A. Boatman [aut, cre], David M. Vock [aut], Joseph S. Koopmeiners [aut]
Maintainer:Jeffrey A. Boatman <jeffrey.boatman at gmail.com>
License:GPL (≥ 3)
NeedsCompilation:yes
Materials:README
In views:CausalInference
CRAN checks:borrowr results

Documentation:

Reference manual:borrowr.html ,borrowr.pdf
Vignettes:Estimating Population Average Treatment Effects with the borrowr Package (source,R code)

Downloads:

Package source: borrowr_0.2.0.tar.gz
Windows binaries: r-devel:borrowr_0.2.0.zip, r-release:borrowr_0.2.0.zip, r-oldrel:borrowr_0.2.0.zip
macOS binaries: r-release (arm64):borrowr_0.2.0.tgz, r-oldrel (arm64):borrowr_0.2.0.tgz, r-release (x86_64):borrowr_0.2.0.tgz, r-oldrel (x86_64):borrowr_0.2.0.tgz
Old sources: borrowr archive

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=borrowrto link to this page.


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