Bayesian Synthetic Control Models R package bscm version 1.0.1 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. Software 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) Jouni Helske <jouni.helske@iki.fi> Comprehensive R Archive Network (CRAN) Jouni Helske [aut, cre] (ORCID: <https://orcid.org/0000-0001-7130-793X>) GPL (>= 3) 2026-08-09 application/tgz https://CRAN.R-project.org/package=bscm doi:10.32614/CRAN.package.bscm