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bscm  

Bayesian Synthetic Control Models
View on CRAN: Click here


Download and install bscm package within the R console
Install from CRAN:
install.packages("bscm")

Install from Github:
library("remotes")
install_github("cran/bscm")

Install by package version:
library("remotes")
install_version("bscm", "1.0.1")



Attach the package and use:
library("bscm")
Maintained by
Jouni Helske
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-08-09
Latest Update: 2026-08-09
Description:
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.
How to cite:
Jouni Helske (2026). bscm: Bayesian Synthetic Control Models. R package version 1.0.1, https://cran.r-project.org/web/packages/bscm. Accessed 10 Nov. 2026.
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Full bscm package functions and examples
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