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Lĩnh vựcSuy luận nhân quảSuy luận nhân quả
HọRegression modelRegression model
Năm ra đời2000s-20152000s–2010s
Người khởi xướngExtended from segmented regression / ITS tradition; multi-break formalization developed across epidemiology and health policy literature (2000s-2010s)Shadish, Cook & Campbell (design framework); Bernal, Cummins & Gasparrini (epidemiological tutorial)
LoạiQuasi-experimental time series regressionQuasi-experimental causal inference
Công trình gốcKontopantelis, E., Doran, T., Springate, D. A., Buchan, I., & Reeves, D. (2015). Regression based quasi-experimental approach when randomisation is not an option: interrupted time series analysis. BMJ, 350, h2750. DOI ↗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 ↗
Tên gọi khácmulti-period ITS, multiple-interruption ITS, segmented time series with multiple breakpoints, MITSpanel ITS, multi-unit ITS, panel ITSA, controlled interrupted time series
Liên quan55
Tóm tắtMulti-period Interrupted Time Series (MITS) extends the classic ITS framework to settings where two or more interventions occur at known time points within the same series. By fitting a segmented regression with multiple breakpoints, MITS estimates the level change and slope change attributable to each intervention while controlling for the underlying secular trend and for the effects of earlier interruptions.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.
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ScholarGateSo sánh phương pháp: Multi-period Interrupted Time Series · Panel Data Interrupted Time Series. Truy cập ngày 2026-06-19 từ https://scholargate.app/vi/compare