방법 비교

	교육 연구에서의 반사실적 영향 평가	시계열 단절 분석 (Interrupted Time Series, ITS)
분야	인과추론	인과추론
계열	Regression model	Regression model
기원 연도	2000s–2010s	2002
창시자	Blundell & Costa Dias; formalized for EU education policy by the European Commission Joint Research Centre	Wagner, Soumerai, Zhang & Ross-Degnan (segmented regression); Bernal, Cummins & Gasparrini (tutorial)
유형	Quasi-experimental causal inference framework	Quasi-experimental segmented regression
원전	Blundell, R., & Costa Dias, M. (2002). Alternative approaches to evaluation in empirical microeconomics. Portuguese Economic Journal, 1(2), 91-115.	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.
별칭	CIE in education, counterfactual program evaluation, causal impact evaluation, education policy impact evaluation	ITS analysis, segmented regression of time series, Kesintili Zaman Serisi (ITS) Analizi
관련	5	5
요약	Counterfactual impact evaluation (CIE) is the systematic application of causal inference designs — such as difference-in-differences, regression discontinuity, matching, and instrumental variables — to measure the genuine effect of education programs, policies, or interventions by constructing a credible counterfactual: what would have happened to participants had they not been treated.	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.