เปรียบเทียบวิธี

	อนุกรมเวลาขัดจังหวะแบบหลายช่วงเวลา	Difference-in-Differences (DiD)
สาขาวิชา	การอนุมานเชิงสาเหตุ	เศรษฐมิติ
ตระกูล	Regression model	Regression model
ปีกำเนิด	2000s-2015	1994
ผู้ริเริ่ม	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)
ประเภท	Quasi-experimental time series regression	Causal inference / panel regression
แหล่งต้นตำรับ	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
ชื่อเรียกอื่น	multi-period ITS, multiple-interruption ITS, segmented time series with multiple breakpoints, MITS	diff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
ที่เกี่ยวข้อง	5	5
สรุป	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.