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Package: bscm 1.0.1

Jouni Helske

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.

Authors:Jouni Helske [aut, cre]

bscm_1.0.1.tar.gz
bscm_1.0.1.zip(r-4.7-x86_64)bscm_1.0.1.zip(r-4.7-arm64)bscm_1.0.1.zip(r-4.6-x86_64)bscm_1.0.1.zip(r-4.6-arm64)
bscm_1.0.1.tar.gz(r-4.7-arm64)bscm_1.0.1.tar.gz(r-4.7-x86_64)bscm_1.0.1.tar.gz(r-4.6-arm64)bscm_1.0.1.tar.gz(r-4.6-x86_64)
bscm_1.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
bscm/json (API)

# Install 'bscm' in R:

install.packages('bscm', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/helske/bscm/issues

Uses libs:

onetbb– Parallelism library for C++
c++– GNU Standard C++ Library v3

Datasets:

fit_single_treated - Example bscmfit object
multiple_treated - Simulated example data with multiple treated units
single_treated - Simulated example data with single treated unit

On CRAN:

onetbb cpp

1.70 score 2 scripts 306 downloads 44 exports 82 dependencies

Last updated from:89d2cec0d4. Checks:10 OK. Indexed: no.

Target	Result	Time
linux-devel-arm64	OK	333
linux-devel-x86_64	OK	398
source / vignettes	OK	337
linux-release-arm64	OK	303
linux-release-x86_64	OK	301
windows-devel-arm64	OK	453
windows-devel-x86_64	OK	423
windows-release-arm64	OK	408
windows-release-x86_64	OK	417
wasm-release	OK	204

Exports:as_draws average_treatment_effect bayes_R2 beta_pr bscm check_mcmc_diagnostics covariate_adjustment covariate_imbalance dirichlet_pr donor_ranking donor_weights effective_donors exponential_pr gamma_pr get_priors get_refmodel get_standata get_stanfit half_normal_pr leave_donor_out lfo log_lik logistic_normal_pr loo loo_R2 nchains ndraws normal_pr placebo_effects plot_coefs plot_effects plot_residuals plot_weights posterior_epred posterior_linpred posterior_predict proj_predict_bscm residual_acf rmse rmse_ratio student_pr synthetic_control treatment_effect tv

Dependencies:abind backports BH boot callr checkmate cli cpp11 data.table desc digest distributional dplyr farver gamm4 generics ggplot2 glue gridExtra gtable gtools inline isoband jsonlite labeling lattice lifecycle lme4 loo magrittr MASS Matrix matrixStats mclogit memisc mgcv minqa mvtnorm nlme nloptr nnet numDeriv ordinal otel pillar pkgbuild pkgconfig posterior processx progressr projpred ps purrr quadprog QuickJSR R6 rbibutils RColorBrewer Rcpp RcppArmadillo RcppEigen RcppParallel Rdpack reformulas rlang rstan rstantools S7 scales StanHeaders stringi stringr tensorA tibble tidyr tidyselect ucminf utf8 vctrs viridisLite withr yaml

Help page	Topics
The 'bscm' package	bscm-package
Return posterior draws from BSCM fit as a draws object	as_draws as_draws.bscmfit
Extract posterior draws of model parameters as a data frame	as.data.frame as.data.frame.bscmfit
Pre- and post-treatment average effects of a Bayesian synthetic control model	average_treatment_effect average_treatment_effect.bscmfit
Estimate Bayesian synthetic control model	bscm
Prior distributions in the Bayesian synthetic control model	beta_pr bscm_prior dirichlet_pr exponential_pr gamma_pr half_normal_pr logistic_normal_pr normal_pr student_pr
Check the validity of the posterior of 'bscmfit' object	check_mcmc_diagnostics check_mcmc_diagnostics.bscmfit
Extract regression coefficients of a Bayesian synthetic control model	coef coef.bscmfit
Covariate adjustments for Bayesian synthetic control model	covariate_adjustment covariate_adjustment.bscmfit
Covariate imbalance of Bayesian synthetic control model	covariate_imbalance covariate_imbalance.bscmfit
Donor ranking	donor_ranking
Extract donor weights of a Bayesian synthetic control model	donor_weights donor_weights.bscmfit
Extract the number of effective donors in a Bayesian synthetic control model	effective_donors effective_donors.bscmfit
Example bscmfit object	fit_single_treated
Expected values of posterior predictive distribution of Bayesian synthetic control model	fitted fitted.bscmfit
Get prior specifications used in the Bayesian synthetic control model	get_priors get_priors.bscmfit
Create a projpred reference model from a BSCM fit	get_refmodel get_refmodel.bscmfit
Get input data to Stan from 'bscmfit' object	get_standata
Extract the 'stanfit' object from the 'bscmfit' object	get_stanfit get_stanfit.bscmfit get_stanfit.default
Leave-out donor sensitivity of a Bayesian synthetic control model	leave_donor_out leave_donor_out.bscmfit
Leave-Future-Out Cross-Validation	lfo lfo.bscmfit
Posterior draws of pointwise log-likelihood	log_lik log_lik.bscmfit
Bayesian R-squared value	bayes_R2 bayes_R2.bscmfit loo_R2 loo_R2.bscmfit
Approximate leave-one-out (LOO) cross-validation for Bayesian synthetic control models	loo loo.bscmfit
Simulated example data with multiple treated units	multiple_treated
Return the number of chains of 'bscmfit' object	nchains nchains.bscmfit
Return the number of posterior draws of a 'bscmfit' object	ndraws ndraws.bscmfit
Placebo effects of a Bayesian synthetic control model	placebo_effects placebo_effects.bscmfit
Visualize regression coefficients of Bayesian synthetic control model	plot_coefs plot_coefs.bscmfit
Visualize BSCM treatment effects	plot_effects plot_effects.bscmfit plot_effects.bscm_ldo plot_effects.bscm_placebo_effects
Visualize BSCM residuals	plot_residuals plot_residuals.bscmfit
Visualize donor weights	plot_weights plot_weights.bscmfit plot_weights.bscm_ldo
Plot Pareto k diagnostics from LFO cross-validation	plot.bscm_lfo
Visualize BSCM estimates	plot plot.bscmfit
Posterior Draws of the Expected Predictive Distribution	posterior_epred posterior_epred.bscmfit
Posterior Draws of the Linear Predictor	posterior_linpred posterior_linpred.bscmfit
Posterior Predictive Distribution of Bayesian Synthetic Control Model	posterior_predict posterior_predict.bscmfit
Print method for LFO cross-validation output	print.bscm_lfo
Print method for bscmfit objects	print.bscmfit print.summary_bscmfit
Print MCMC Diagnostics	print.bscmfit_diagnostics
Predictions from a projected BSCM model	proj_predict_bscm
Autocorrelation function for residuals of BSCM	residual_acf
Posterior residuals of a Bayesian synthetic control model	residuals residuals.bscmfit
Extract root mean squared errors of a Bayesian synthetic control model	rmse rmse.bscmfit
Extract the ratio of post- to pre-treatment RMSE	rmse_ratio rmse_ratio.bscmfit
Extract residual standard deviations of a Bayesian synthetic control model	sigma sigma.bscmfit
Simulated example data with single treated unit	single_treated
Summarise posterior draws of an estimated Bayesian synthetic control model	summary summary.bscmfit
Synthetic control series of a Bayesian synthetic control model	synthetic_control synthetic_control.bscmfit
Treatment effect estimates of a Bayesian synthetic control model	treatment_effect treatment_effect.bscmfit
Define the time-varying coefficients for BSCM	tv

Package: bscm 1.0.1

bscm: Bayesian Synthetic Control Models

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