เปรียบเทียบวิธี

	อนุกรมเวลาขัดจังหวะแบบหลายช่วงเวลา	อนุกรมเวลาที่ถูกขัดจังหวะแบบข้อมูลแผง
สาขาวิชา	การอนุมานเชิงสาเหตุ	การอนุมานเชิงสาเหตุ
ตระกูล	Regression model	Regression model
ปีกำเนิด	2000s-2015	2000s–2010s
ผู้ริเริ่ม	Extended 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)
ประเภท	Quasi-experimental time series regression	Quasi-experimental causal inference
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.	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.
ชื่อเรียกอื่น	multi-period ITS, multiple-interruption ITS, segmented time series with multiple breakpoints, MITS	panel ITS, multi-unit ITS, panel ITSA, controlled interrupted time series
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.	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.