ScholarGate
Ассистент

Сравнение методов

Просматривайте выбранные методы рядом; строки с различиями подсвечены.

Оценка политики с помощью прерванной временной серии×Анализ прерванных временных рядов (Interrupted Time Series, ITS)×
ОбластьПричинно-следственный выводПричинно-следственный вывод
СемействоRegression modelRegression model
Год появления1975 (intervention analysis); 2000s–2010s (policy evaluation framing)2002
Автор методаBox & 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)
ТипQuasi-experimental causal designQuasi-experimental segmented regression
Основополагающий источникBernal, 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 ↗
Другие названияITS for policy evaluation, policy ITS, segmented regression for policy, policy impact ITSITS analysis, segmented regression of time series, Kesintili Zaman Serisi (ITS) Analizi
Связанные45
СводкаInterrupted 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.
ScholarGateНабор данных
  1. v1
  2. 2 Источники
  3. PUBLISHED
  1. v1
  2. 2 Источники
  3. PUBLISHED

Перейти к поиску Скачать слайды

ScholarGateСравнение методов: Policy Evaluation Interrupted Time Series · Interrupted Time Series. Получено 2026-06-19 из https://scholargate.app/ru/compare