Porównaj metody

	Wielookresowa przerywana analiza szeregów czasowych	Metoda różnic w różnicach (Diff-in-Diff)
Dziedzina	Wnioskowanie przyczynowe	Ekonometria
Rodzina	Regression model	Regression model
Rok powstania	2000s-2015	1994
Twórca	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)
Typ	Quasi-experimental time series regression	Causal inference / panel regression
Źródło pierwotne	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
Inne nazwy	multi-period ITS, multiple-interruption ITS, segmented time series with multiple breakpoints, MITS	diff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
Pokrewne	5	5
Podsumowanie	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.