borrowr (0.1.0)

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Estimate Causal Effects with Borrowing Between Data Sources.

http://cran.r-project.org/web/packages/borrowr

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) .

Maintainer: Jeffrey A. Boatman
Author(s): Jeffrey A. Boatman [aut, cre], David M. Vock [aut], Joseph S. Koopmeiners [aut]

License: GPL (>= 3)

Uses: Rcpp, ggplot2, knitr, rmarkdown

Released about 1 month ago.


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