Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Синтетичний контрольний метод у дослідженнях освіти× | Аналіз перерваних часових рядів (ITS)× | |
|---|---|---|
| Галузь | Причинно-наслідковий висновок | Причинно-наслідковий висновок |
| Родина | Regression model | Regression model |
| Рік появи≠ | 2003-2010 | 2002 |
| Автор методу≠ | Alberto Abadie, Alexis Diamond, and Jens Hainmueller | Wagner, Soumerai, Zhang & Ross-Degnan (segmented regression); Bernal, Cummins & Gasparrini (tutorial) |
| Тип≠ | Quasi-experimental causal inference | Quasi-experimental segmented regression |
| Основоположне джерело≠ | 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 ↗ |
| Інші назви≠ | SCM in education, synthetic control, synthetic comparator, SCM | ITS analysis, segmented regression of time series, Kesintili Zaman Serisi (ITS) Analizi |
| Пов'язані | 5 | 5 |
| Підсумок≠ | The Synthetic Control Method (SCM) estimates the causal effect of an education policy or intervention by constructing a weighted combination of untreated comparison units — the synthetic control — that closely mimics the treated unit's pre-intervention trajectory. Developed by Abadie, Diamond, and Hainmueller, it is especially valuable when only one or a small number of schools, districts, or countries receive a policy change and no natural comparison 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. |
| ScholarGateНабір даних ↗ |
|
|