Bayesian Synthetic Control Models
Overview
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.
- Initial CRAN submission.
From NEWS.md in the release
Install
Health
- OK13 OKNow
- OK8 OK2026-08-10
Documentation
- Help pages
- 51includes a package overview page
- Examples that run
- 94%29 run in a plain check · 2 only when donttest examples are enabled (R CMD check --as-cran)
- Exported functions with examples
- 61%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 10%
Downloads
Repository
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Dependencies
Code & Tests
Datasets
People & History
- 1.0.1Latest2026-08-09 · current release
- RR 4.6.0 released · 2026-04-24
Package metadata
- First published
- 2026-08-09
- Total releases
- 1 / 1 yrs
- License
- GPL (>= 3) OSI
- Minimum R
- ≥ 4.1.0
- Bundled data
- 3.4 MB / 3 files
- Download size
- 3.5 MB
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