The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.

PSPI: Propensity Score Predictive Inference for Generalizability

Provides a suite of Propensity Score Predictive Inference (PSPI) methods to generalize treatment effects in trials to target populations. The package includes an existing model Bayesian Causal Forest (BCF) and four PSPI models (BCF-PS, FullBART, SplineBART, DSplineBART). These methods leverage Bayesian Additive Regression Trees (BART) to adjust for high-dimensional covariates and nonlinear associations, while SplineBART and DSplineBART further use propensity score based splines to address covariate shift between trial data and target population.

Version: 1.2
Depends: R (≥ 4.1.0)
Imports: Rcpp, arm, dplyr, mvtnorm, stringr, stats, nnet, methods
LinkingTo: Rcpp, RcppArmadillo, RcppDist, RcppProgress, pg
Suggests: knitr, rmarkdown, mitml
Published: 2025-12-02
DOI: 10.32614/CRAN.package.PSPI
Author: Jungang Zou [aut, cre], Qixuan Chen [aut], Joseph Schwartz [aut], Nathalie Moise [aut], Roderick Little [aut], Robert McCulloch [ctb], Rodney Sparapani [ctb], Charles Spanbauer [ctb], Robert Gramacy [ctb], Jean-Sebastien Roy [ctb]
Maintainer: Jungang Zou <jungang.zou at gmail.com>
License: GPL-2
NeedsCompilation: yes
SystemRequirements: GNU make
Materials: README, NEWS
CRAN checks: PSPI results

Documentation:

Reference manual: PSPI.html , PSPI.pdf

Downloads:

Package source: PSPI_1.2.tar.gz
Windows binaries: r-devel: PSPI_1.1.zip, r-release: not available, r-oldrel: PSPI_1.1.zip
macOS binaries: r-release (arm64): PSPI_1.2.tgz, r-oldrel (arm64): PSPI_1.2.tgz, r-release (x86_64): PSPI_1.2.tgz, r-oldrel (x86_64): PSPI_1.2.tgz
Old sources: PSPI archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=PSPI to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.