Comparer des méthodes

	Les séries chronologiques interrompues en recherche sur l'éducation	Méthode du Contrôle Synthétique (MCS)
Domaine	Inférence causale	Inférence causale
Famille	Regression model	Regression model
Année d'origine	1979-2002	2003–2010
Auteur d'origine	Shadish, Cook & Campbell (quasi-experimental design); Wagner et al. (segmented regression formalization)	Alberto Abadie & Javier Gardeazabal (2003); Abadie, Diamond & Hainmueller (2010)
Type	Quasi-experimental causal inference	Quasi-experimental causal inference
Source fondatrice	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.
Alias	ITS in education, educational ITS, segmented regression in education, policy interrupted time series	SCM, synthetic control, synth estimator, Abadie-Diamond-Hainmueller method
Apparentées	4	4
Résumé	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.