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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>.
Browse package contents
Package details |
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| Author | Jeffrey A. Boatman [aut, cre], David M. Vock [aut], Joseph S. Koopmeiners [aut] |
| Maintainer | Jeffrey A. Boatman <jeffrey.boatman@gmail.com> |
| License | GPL (>= 3) |
| Version | 0.2.0 |
| Package repository | View on CRAN |
| Installation |
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