Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Переривчаста часова серія (ITS) для оцінки політики× | Аналіз перерваних часових рядів (ITS)× | |
|---|---|---|
| Галузь | Причинно-наслідковий висновок | Причинно-наслідковий висновок |
| Родина | Regression model | Regression model |
| Рік появи≠ | 1975 (intervention analysis); 2000s–2010s (policy evaluation framing) | 2002 |
| Автор методу≠ | Box & Tiao (1975); popularised for policy by Shadish, Cook & Campbell (2002) and Bernal et al. (2017) | Wagner, Soumerai, Zhang & Ross-Degnan (segmented regression); Bernal, Cummins & Gasparrini (tutorial) |
| Тип≠ | Quasi-experimental causal design | Quasi-experimental segmented regression |
| Основоположне джерело | 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 ↗ | 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≠ | ITS for policy evaluation, policy ITS, segmented regression for policy, policy impact ITS | ITS analysis, segmented regression of time series, Kesintili Zaman Serisi (ITS) Analizi |
| Пов'язані≠ | 4 | 5 |
| Підсумок≠ | Interrupted Time Series (ITS) for policy evaluation uses routinely collected aggregate time-series data to estimate the causal impact of a policy change. A segmented regression model splits the series at a known intervention date, estimating both an immediate level shift and a change in trend attributable to the policy — without requiring a randomised control group. | 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 ↗ |
|
|