Comparer des méthodes

	Interrupted Time Series in Crime Analysis	Analyse de séries chronologiques interrompues (ITS)
Domaine	Criminology	Inférence causale
Famille	Process / pipeline	Regression model
Année d'origine	1980	2002
Auteur d'origine	George E. P. Box & George C. Tiao (intervention analysis); David McDowall, Richard McCleary, and colleagues (criminological text)	Wagner, Soumerai, Zhang & Ross-Degnan (segmented regression); Bernal, Cummins & Gasparrini (tutorial)
Type	Quasi-experimental evaluation of a policy effect on a time series	Quasi-experimental segmented regression
Source fondatrice	McDowall, D., McCleary, R., Meidinger, E. E., & Hay, R. A. (1980). Interrupted Time Series Analysis. Sage Publications. ISBN: 9780803914933	Bernal, J. L., 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.
Alias	Crime Intervention Analysis, ITS Crime Evaluation, Quasi-Experimental Time Series for Crime, Pre-Post Crime Trend Analysis	ITS analysis, segmented regression of time series, Kesintili Zaman Serisi (ITS) Analizi
Apparentées	4	5
Résumé	Interrupted time series (ITS) analysis evaluates whether a law, policy, or intervention changed the course of a crime series. By modeling the level and slope of crime before and after a dated 'interruption' — a gun-control law, a policing crackdown, a sentencing reform — it tests whether the series jumped or bent at that moment relative to its prior trend. Box and Tiao formalized intervention analysis in 1975, and McDowall, McCleary, and colleagues brought the method to criminology in their widely used 1980 monograph.	Interrupted Time Series analysis is a quasi-experimental design that estimates the effect of a single, well-dated intervention by comparing the trajectory of an outcome before and after it occurs. Formalised as segmented regression by Wagner and colleagues (2002) and popularised as a public-health evaluation tutorial by Bernal, Cummins and Gasparrini (2017), it separates the intervention's impact into a change in level and a change in slope.