Comparer des méthodes

	Test placebo en recherche en éducation	Méthode du Contrôle Synthétique (MCS)
Domaine	Inférence causale	Inférence causale
Famille	Regression model	Regression model
Année d'origine	1990s–2000s	2003–2010
Auteur d'origine	Widely adopted in applied econometrics and education research; codified by Imbens, Wooldridge, Lee, and Lemieux	Alberto Abadie & Javier Gardeazabal (2003); Abadie, Diamond & Hainmueller (2010)
Type	Falsification / robustness check	Quasi-experimental causal inference
Source fondatrice	Imbens, G. W., & Wooldridge, J. M. (2009). Recent Developments in the Econometrics of Program Evaluation. Journal of Economic Literature, 47(1), 5-86.	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	placebo regression, falsification test, placebo check, fake-treatment test	SCM, synthetic control, synth estimator, Abadie-Diamond-Hainmueller method
Apparentées	4	4
Résumé	A placebo test is a falsification check used in quasi-experimental education research to validate a causal design. By applying the same estimator to a time period, group, or outcome where no real effect should exist, researchers verify that their identification strategy is not picking up spurious patterns. A statistically significant placebo estimate signals a flaw in the design, while a null result supports its credibility.	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.