bscm: Bayesian Synthetic Control Models

Implements the synthetic control method of Abadie, Diamond, and Hainmueller (2010) <doi:10.1198/jasa.2009.ap08746> within a Bayesian framework, enabling straightforward uncertainty quantification of treatment effects and other quantities of interest. Supports time-varying covariates with potentially time-varying effects, single or multiple treated units, and staggered treatment adoption. Provides methods for model assessment, comparison, and selection based on placebo studies, cross-validation, and posterior predictive checks. Posterior sampling is performed using Markov chain Monte Carlo via Stan.

Version: 1.0.1
Depends: R (≥ 4.1.0)
Imports: checkmate, cli, dplyr, ggplot2, loo, methods, posterior, progressr, projpred, quadprog, Rcpp (≥ 0.12.0), RcppParallel (≥ 5.0.1), rlang, rstan (≥ 2.32.7), rstantools (≥ 2.6.0), tidyr
LinkingTo: BH (≥ 1.66.0), Rcpp (≥ 0.12.0), RcppEigen (≥ 0.3.3.3.0), RcppParallel (≥ 5.0.1), rstan (≥ 2.32.7), StanHeaders (≥ 2.32.10)
Suggests: testthat (≥ 3.0.0)
Published: 2026-08-09
DOI: 10.32614/CRAN.package.bscm (may not be active yet)
Author: Jouni Helske ORCID iD [aut, cre]
Maintainer: Jouni Helske <jouni.helske at iki.fi>
BugReports: https://github.com/helske/bscm/issues
License: GPL (≥ 3)
URL: https://github.com/helske/bscm
NeedsCompilation: yes
SystemRequirements: GNU make
Materials: README, NEWS
CRAN checks: bscm results

Documentation:

Reference manual: bscm.html , bscm.pdf

Downloads:

Package source: bscm_1.0.1.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): bscm_1.0.1.tgz, r-oldrel (arm64): bscm_1.0.1.tgz, r-release (x86_64): bscm_1.0.1.tgz, r-oldrel (x86_64): bscm_1.0.1.tgz

Linking:

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