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| 합성 통제 방법 (SCM)× | 시계열 단절 분석 (Interrupted Time Series, ITS)× | |
|---|---|---|
| 분야 | 인과추론 | 인과추론 |
| 계열 | Regression model | Regression model |
| 기원 연도≠ | 2010 | 2002 |
| 창시자≠ | Abadie, Diamond & Hainmueller | Wagner, Soumerai, Zhang & Ross-Degnan (segmented regression); Bernal, Cummins & Gasparrini (tutorial) |
| 유형≠ | Counterfactual causal-inference model | Quasi-experimental segmented regression |
| 원전≠ | 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. DOI ↗ | 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. DOI ↗ |
| 별칭≠ | synthetic control method, SCM, synthetic counterfactual, Sentetik Kontrol Yöntemi (SCM) | ITS analysis, segmented regression of time series, Kesintili Zaman Serisi (ITS) Analizi |
| 관련 | 5 | 5 |
| 요약≠ | 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. |
| ScholarGate데이터셋 ↗ |
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