Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Interrupted Time Series in Crime Analysis× | Анализ прерванных временных рядов (Interrupted Time Series, ITS)× | |
|---|---|---|
| Область≠ | Criminology | Причинно-следственный вывод |
| Семейство≠ | Process / pipeline | Regression model |
| Год появления≠ | 1980 | 2002 |
| Автор метода≠ | George E. P. Box & George C. Tiao (intervention analysis); David McDowall, Richard McCleary, and colleagues (criminological text) | Wagner, Soumerai, Zhang & Ross-Degnan (segmented regression); Bernal, Cummins & Gasparrini (tutorial) |
| Тип≠ | Quasi-experimental evaluation of a policy effect on a time series | Quasi-experimental segmented regression |
| Основополагающий источник≠ | McDowall, D., McCleary, R., Meidinger, E. E., & Hay, R. A. (1980). Interrupted Time Series Analysis. Sage Publications. ISBN: 9780803914933 | 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 ↗ |
| Другие названия≠ | Crime Intervention Analysis, ITS Crime Evaluation, Quasi-Experimental Time Series for Crime, Pre-Post Crime Trend Analysis | ITS analysis, segmented regression of time series, Kesintili Zaman Serisi (ITS) Analizi |
| Связанные≠ | 4 | 5 |
| Сводка≠ | Interrupted time series (ITS) analysis evaluates whether a law, policy, or intervention changed the course of a crime series. By modeling the level and slope of crime before and after a dated 'interruption' — a gun-control law, a policing crackdown, a sentencing reform — it tests whether the series jumped or bent at that moment relative to its prior trend. Box and Tiao formalized intervention analysis in 1975, and McDowall, McCleary, and colleagues brought the method to criminology in their widely used 1980 monograph. | 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. |
| ScholarGateНабор данных ↗ |
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