Interrupted time series
Interrupted time series analysis sometimes known as quasi-experimental time series analysis is an approach for the analysis of a single time series of data known to be affected by interventions (interrupted time series, ITS). [1] The interrupted time series design is the design of experiments based on the interrupted time series approach.
Applications include various research in social sciences:
- political science: impact of changes in laws on the behavior of people;[1] see, e.g., Effectiveness of sex offender registration policies in the United States#Interrupted time series analysis studies.
- economics: impact of changes in credit controls on borrowing behavior[1]
- sociology: impact of experiments in income maintenance on the behavior of participants in welfare programs[1]
- history: impact of major historical events on the behavior of those affected by the events[1]
- medicine: in medical research, medical treatment is an intervention whose effect are to be studied
The ITS design is the base of the comparative time series design, whereby there is a control series and an interrupted series, and the effect of an intervention is confirmed by the control series. [2]
Effects of the intervention are evaluated by changes in the level and slope of the time series and statistical significance of the intervention parameters. [3]