Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Метод прерванного временного ряда на панельных данных× | Модель с фиксированными эффектами для панельных данных× | |
|---|---|---|
| Область≠ | Причинно-следственный вывод | Эконометрика |
| Семейство | Regression model | Regression model |
| Год появления≠ | 2000s–2010s | 2014 |
| Автор метода≠ | Shadish, Cook & Campbell (design framework); Bernal, Cummins & Gasparrini (epidemiological tutorial) | Hsiao (textbook treatment); within transformation of panel data |
| Тип≠ | Quasi-experimental causal inference | Panel data regression |
| Основополагающий источник≠ | Lopez Bernal, J., 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 ↗ | Hsiao, C. (2014). Analysis of Panel Data (3rd ed.). Cambridge University Press. DOI ↗ |
| Другие названия | panel ITS, multi-unit ITS, panel ITSA, controlled interrupted time series | fixed effects model, within estimator, panel fixed-effects regression, Panel Veri — Sabit Etkiler Modeli |
| Связанные | 5 | 5 |
| Сводка≠ | Panel Data Interrupted Time Series (panel ITS) is a quasi-experimental method that estimates the causal effect of an intervention using repeated observations from multiple units over time. By exploiting variation across both units and time periods, it provides stronger causal identification than single-unit ITS, detecting changes in the level and slope of the outcome trajectory immediately following a clearly dated intervention. | The Panel Data Fixed Effects model estimates relationships from panel data (the same units observed over several time periods) while controlling for unit- and/or time-specific effects, supporting causal inference. It is developed as the within estimator in standard treatments such as Hsiao's Analysis of Panel Data (2014). |
| ScholarGateНабор данных ↗ |
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