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) <doi10.1093/biostatistics/kxx031>.
| Version: | 0.1.1 |
| Depends: | R (≥ 3.5.0) |
| Imports: | mvtnorm (≥ 1.0.8), BART (≥ 2.1), Rcpp (≥ 1.0.0) |
| LinkingTo: | Rcpp |
| Suggests: | knitr, rmarkdown, ggplot2 |
| Published: | 2019-10-30 |
| Author: | Jeffrey A. Boatman [aut, cre], David M. Vock [aut], Joseph S. Koopmeiners [aut] |
| Maintainer: | Jeffrey A. Boatman <boat0036 at umn.edu> |
| License: | GPL (≥ 3) |
| NeedsCompilation: | yes |
| Materials: | README |
| CRAN checks: | borrowr results |
| Reference manual: | borrowr.pdf |
| Vignettes: |
Estimating Population Average Treatment Effects with the borrowr Package |
| Package source: | borrowr_0.1.1.tar.gz |
| Windows binaries: | r-devel: borrowr_0.1.1.zip, r-release: borrowr_0.1.1.zip, r-oldrel: borrowr_0.1.1.zip |
| macOS binaries: | r-release: borrowr_0.1.1.tgz, r-oldrel: borrowr_0.1.1.tgz |
| Old sources: | borrowr archive |
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