PSAboot: Bootstrapping for Propensity Score Analysis

It is often advantageous to test a hypothesis more than once in the context of propensity score analysis (Rosenbaum, 2012) <doi:10.1093/biomet/ass032>. The functions in this package facilitate bootstrapping for propensity score analysis (PSA). By default, bootstrapping using two classification tree methods (using 'rpart' and 'ctree' functions), two matching methods (using 'Matching' and 'MatchIt' packages), and stratification with logistic regression. A framework is described for users to implement additional propensity score methods. Visualizations are emphasized for diagnosing balance; exploring the correlation relationships between bootstrap samples and methods; and to summarize results.

Version: 1.3.8
Depends: ggplot2, graphics, PSAgraphics, R (≥ 3.0)
Imports: ggthemes, Matching, MatchIt, modeltools, parallel, party, psych, reshape2, rpart, stats, TriMatch, utils
Suggests: knitr, rmarkdown
Published: 2023-10-23
Author: Jason Bryer ORCID iD [aut, cre]
Maintainer: Jason Bryer <jason at>
License: GPL-2 | GPL-3 [expanded from: GPL]
NeedsCompilation: no
Materials: NEWS
CRAN checks: PSAboot results


Reference manual: PSAboot.pdf
Vignettes: Impact of Data Order for Propensity Score Matching
Bootstrapping for Propensity Score Analysiss


Package source: PSAboot_1.3.8.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): PSAboot_1.3.8.tgz, r-oldrel (arm64): PSAboot_1.3.8.tgz, r-release (x86_64): PSAboot_1.3.8.tgz, r-oldrel (x86_64): not available
Old sources: PSAboot archive


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