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) . For information on MEMs, see Kaizer, Koopmeiners, & Hobbs (2018) .


Reference manual

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0.1.0 by Jeffrey A. Boatman, a month ago

Browse source code at

Authors: Jeffrey A. Boatman [aut, cre] , David M. Vock [aut] , Joseph S. Koopmeiners [aut]

Documentation:   PDF Manual  

GPL (>= 3) license

Imports mvtnorm, BART, Rcpp

Suggests knitr, rmarkdown, ggplot2

Linking to Rcpp

See at CRAN