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>.

Package details

AuthorJeffrey A. Boatman [aut, cre], David M. Vock [aut], Joseph S. Koopmeiners [aut]
MaintainerJeffrey A. Boatman <>
LicenseGPL (>= 3)
Package repositoryView on CRAN
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borrowr documentation built on Dec. 8, 2020, 5:08 p.m.