So sánh phương pháp

	Chuỗi thời gian bị gián đoạn nhiều giai đoạn	Phương pháp Sai phân kép (Difference-in-Differences - DiD)
Lĩnh vực	Suy luận nhân quả	Kinh tế lượng
Họ	Regression model	Regression model
Năm ra đời	2000s-2015	1994
Người khởi xướng	Extended from segmented regression / ITS tradition; multi-break formalization developed across epidemiology and health policy literature (2000s-2010s)	Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
Loại	Quasi-experimental time series regression	Causal inference / panel regression
Công trình gốc	Kontopantelis, 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.	Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355
Tên gọi khác	multi-period ITS, multiple-interruption ITS, segmented time series with multiple breakpoints, MITS	diff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
Liên quan	5	5
Tóm tắt	Multi-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.	Difference-in-Differences is a causal-inference method that estimates the effect of an intervention by comparing how a treatment group and a control group change over time. Made famous by Card and Krueger's 1994 minimum-wage study and developed in Angrist and Pischke's Mostly Harmless Econometrics, it isolates the treatment effect as the difference between the two groups' before-after changes.