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.
- Version0.2.0
- R version≥ 3.5.0
- LicenseGPL (≥ 3)
- Needs compilation?Yes
- Last release12/08/2020
Documentation
Team
Jeffrey A. Boatman
David M. Vock
Show author detailsRolesAuthorJoseph S. Koopmeiners
Show author detailsRolesAuthor
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- Imports3 packages
- Suggests3 packages
- Linking To1 package