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>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.2.0 |
rolling linux/jammy R-4.5 | borrowr_0.2.0.tar.gz |
199.1 KiB |
0.2.0 |
rolling linux/noble R-4.5 | borrowr_0.2.0.tar.gz |
200.5 KiB |
0.2.0 |
rolling source/ R- | borrowr_0.2.0.tar.gz |
94.5 KiB |
0.2.0 |
latest linux/jammy R-4.5 | borrowr_0.2.0.tar.gz |
199.1 KiB |
0.2.0 |
latest linux/noble R-4.5 | borrowr_0.2.0.tar.gz |
200.5 KiB |
0.2.0 |
latest source/ R- | borrowr_0.2.0.tar.gz |
94.5 KiB |
0.2.0 |
2026-04-26 source/ R- | borrowr_0.2.0.tar.gz |
94.5 KiB |
0.2.0 |
2026-04-23 source/ R- | borrowr_0.2.0.tar.gz |
94.5 KiB |
0.2.0 |
2026-04-09 windows/windows R-4.5 | borrowr_0.2.0.zip |
521.4 KiB |
0.2.0 |
2025-04-20 source/ R- | borrowr_0.2.0.tar.gz |
94.5 KiB |