Võrdle meetodeid

	Sünteetilise kontrolli meetod (SCM)	Katkendliku ajasarja (ITS) analüüs
Valdkond	Põhjuslik järeldamine	Põhjuslik järeldamine
Perekond	Regression model	Regression model
Tekkeaasta	2010	2002
Looja	Abadie, Diamond & Hainmueller	Wagner, Soumerai, Zhang & Ross-Degnan (segmented regression); Bernal, Cummins & Gasparrini (tutorial)
Tüüp	Counterfactual causal-inference model	Quasi-experimental segmented regression
Algallikas	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.	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.
Rööpnimetused	synthetic control method, SCM, synthetic counterfactual, Sentetik Kontrol Yöntemi (SCM)	ITS analysis, segmented regression of time series, Kesintili Zaman Serisi (ITS) Analizi
Seotud	5	5
Kokkuvõte	The Synthetic Control Method, introduced by Abadie, Diamond and Hainmueller in 2010, builds a weighted counterfactual for a single treated unit from a pool of untreated donor units. It is widely regarded as the gold standard for evaluating large policy interventions, natural experiments, and N=1 case studies where no obvious comparison unit exists.	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.