Compara mètodes

	Anàlisi d'Impacte Causal Bayesiana	Anàlisi de Sèries Temporals Interrompudes (ITS)
Camp	Inferència causal	Inferència causal
Família	Regression model	Regression model
Any d'origen	2015	2002
Autor original	Brodersen, Gallusser, Koehler, Remy & Scott (Google)	Wagner, Soumerai, Zhang & Ross-Degnan (segmented regression); Bernal, Cummins & Gasparrini (tutorial)
Tipus	Bayesian causal inference / time series	Quasi-experimental segmented regression
Font seminal	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.	Bernal, J. L., Cummins, S., & Gasparrini, A. (2017). Interrupted time series regression for the evaluation of public health interventions: a tutorial. International Journal of Epidemiology, 46(1), 348-355.
Àlies	CausalImpact, Bayesian structural time series causal inference, BSTS causal impact, Bayesian intervention analysis	ITS analysis, segmented regression of time series, Kesintili Zaman Serisi (ITS) Analizi
Relacionats	4	5
Resum	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.	Interrupted Time Series analysis is a quasi-experimental design that estimates the effect of a single, well-dated intervention by comparing the trajectory of an outcome before and after it occurs. Formalised as segmented regression by Wagner and colleagues (2002) and popularised as a public-health evaluation tutorial by Bernal, Cummins and Gasparrini (2017), it separates the intervention's impact into a change in level and a change in slope.