Package: PSPI
Type: Package
Title: Propensity Score Predictive Inference for Generalizability
Version: 1.2
Date: 2025-11-15
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]
Authors@R: c(person("Jungang", "Zou", role = c("aut", "cre"), email = "jungang.zou@gmail.com"), person("Qixuan", "Chen", role = "aut"), person("Joseph", "Schwartz", role = "aut"), person("Nathalie", "Moise", role = "aut"), person("Roderick", "Little", role = "aut"), person("Robert", "McCulloch", role = "ctb"), person("Rodney", "Sparapani", role = "ctb"), person("Charles", "Spanbauer", role = "ctb"), person("Robert", "Gramacy", role = "ctb"), person("Jean-Sebastien", "Roy", role = "ctb"))
Maintainer: Jungang Zou <jungang.zou@gmail.com>
Description: 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. 
License: GPL-2
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: Rcpp, arm, dplyr, mvtnorm, stringr, stats, nnet, methods
LinkingTo: Rcpp, RcppArmadillo, RcppDist, RcppProgress, pg
RoxygenNote: 7.3.2
SystemRequirements: GNU make
Suggests: knitr, rmarkdown, mitml
NeedsCompilation: yes
Packaged: 2025-12-01 19:21:26 UTC; jz3183
Repository: CRAN
Date/Publication: 2025-12-02 07:50:21 UTC
Built: R 4.6.0; aarch64-apple-darwin23; 2026-04-26 14:37:02 UTC; unix
Archs: PSPI.so.dSYM
