Linganisha mbinu

	Uchambuzi wa Kitakwimu wa Athari za Kiusababishi kwa Kutumia Mbinu ya Bayesian	Njia ya Kidhibiti Sanisi (SCM)
Nyanja	Uhitimisho wa Kisababishi	Uhitimisho wa Kisababishi
Familia	Regression model	Regression model
Mwaka wa asili	2015	2003–2010
Mwanzilishi	Brodersen, Gallusser, Koehler, Remy & Scott (Google)	Alberto Abadie & Javier Gardeazabal (2003); Abadie, Diamond & Hainmueller (2010)
Aina	Bayesian causal inference / time series	Quasi-experimental causal inference
Chanzo asilia	Brodersen, K. H., Gallusser, F., Koehler, J., Remy, N., & Scott, S. L. (2015). Inferring causal impact using Bayesian structural time-series models. Annals of Applied Statistics, 9(1), 247-274.	Abadie, A., Diamond, A., & Hainmueller, J. (2010). Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California's Tobacco Control Program. Journal of the American Statistical Association, 105(490), 493-505.
Majina mbadala	CausalImpact, Bayesian structural time series causal inference, BSTS causal impact, Bayesian intervention analysis	SCM, synthetic control, synth estimator, Abadie-Diamond-Hainmueller method
Zinazohusiana	4	4
Muhtasari	Bayesian Causal Impact Analysis uses a Bayesian structural time series (BSTS) model to estimate the causal effect of an intervention on a time series outcome. Developed by Brodersen and colleagues at Google in 2015, it builds a probabilistic counterfactual — what the series would have looked like without the intervention — from pre-intervention data and optional control covariates, then compares it with the observed post-intervention values to produce a fully Bayesian posterior over the causal effect.	The Synthetic Control Method estimates the causal effect of a treatment or policy on a single treated unit by constructing a weighted combination of untreated units — the synthetic control — that closely resembles the treated unit before the intervention. The gap between the treated unit and its synthetic counterpart after the intervention is the estimated treatment effect.