Package: borrowr
Type: Package
Title: Estimate Causal Effects with Borrowing Between Data Sources
Version: 0.2.0
Author: Jeffrey A. Boatman [aut, cre],
  David M. Vock [aut],
  Joseph S. Koopmeiners [aut]
Maintainer: Jeffrey A. Boatman <jeffrey.boatman@gmail.com>
Description: 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>.
Depends: R (>= 3.5.0)
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: mvtnorm(>= 1.0.8), BART(>= 2.1), Rcpp (>= 1.0.0)
LinkingTo: Rcpp
Suggests: knitr, rmarkdown, ggplot2
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2020-12-08 00:09:56 UTC; Jeff
Repository: CRAN
Date/Publication: 2020-12-08 12:50:03 UTC
Built: R 4.4.3; x86_64-w64-mingw32; 2025-11-01 03:30:15 UTC; windows
Archs: x64
