Compară metode

	Serii de timp întrerupte în cercetarea educațională	Metoda Controlului Sintetic (MCS)
Domeniu	Inferență cauzală	Inferență cauzală
Familie	Regression model	Regression model
Anul apariției	1979-2002	2003–2010
Autorul original	Shadish, Cook & Campbell (quasi-experimental design); Wagner et al. (segmented regression formalization)	Alberto Abadie & Javier Gardeazabal (2003); Abadie, Diamond & Hainmueller (2010)
Tip	Quasi-experimental causal inference	Quasi-experimental causal inference
Sursa seminală	Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and Quasi-Experimental Designs for Generalized Causal Inference. Houghton Mifflin. ISBN: 978-0395615560	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.
Denumiri alternative	ITS in education, educational ITS, segmented regression in education, policy interrupted time series	SCM, synthetic control, synth estimator, Abadie-Diamond-Hainmueller method
Înrudite	4	4
Rezumat	Interrupted time series (ITS) analysis is a quasi-experimental design that estimates the causal effect of an education policy or intervention by examining whether an outcome trend changes abruptly at the point of implementation. Applied to education, it is used to evaluate reforms, curriculum changes, testing policies, and school interventions using routinely collected longitudinal data without a randomised control group.	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.