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borrowr
View on CRAN: Click
here
Download and install borrowr package within the R console
Install from CRAN:
install.packages("borrowr")
Install from Github:
library("remotes")
install_github("cran/borrowr") Install by package version:
library("remotes")
install_version("borrowr", "0.2.0") Attach the package and use:
library("borrowr")
Maintained by
Jeffrey A. Boatman
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-07-19
Latest Update: 2020-12-08
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) .
For information on MEMs, see Kaizer, Koopmeiners, &
Hobbs (2018) .
How to cite:
Jeffrey A. Boatman (2019). borrowr: Estimate Causal Effects with Borrowing Between Data Sources. R package version 0.2.0, https://cran.r-project.org/web/packages/borrowr. Accessed 06 Mar. 2026.
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Other R packages that borrowr depends,
imports, suggests or enhances
Complete documentation for borrowr
Functions, R codes and Examples using
the borrowr R package
Some associated functions: adapt . credint . pate .
Some associated R codes: RcppExports.R . bart.R . bayes_lm.R . credint.R . data.R . fit_mems.R . methods.R . pate.R . posterior-functions.R . tree_funs.R . utils.R . wbart.R . Full borrowr package functions and examples
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