Description
Estimate Causal Effects with Borrowing Between Data Sources.
Description
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>.
README.md
borrowr
R package for estimating the population average treatment effect using a primary data source with borrowing from supplemental data sources.
To install from source and build vignettes:
devtools::install_github("jeffrey-boatman/borrowr", build = TRUE, build_opts = c("--no-resave-data", "--no-manual"), force = TRUE)
To do:
- update documentation (changes included: adding argument for prior probability of exchangeability, updated gamma prior for bayesian linear model, ...)