Interrupted time series
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Interrupted time series analysis (ITS), sometimes known as quasi-experimental time series analysis, is a method of statistical analysis involving tracking a long-term period before and after a point of intervention to assess the intervention's effects. The time series refers to the data over the period, while the interruption is the intervention, which is a controlled external influence or set of influences.[1][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] Interrupted time series design is the design of experiments based on the interrupted time series approach.
The method is used in various areas of research, such as:
- political science: impact of changes in laws on the behavior of people;[2] (e.g., Effectiveness of sex offender registration policies in the United States)
- economics: impact of changes in credit controls on borrowing behavior;[2]
- sociology: impact of experiments in income maintenance on the behavior of participants in welfare programs;[2]
- history: impact of major historical events on the behavior of those affected by the events;[2]
- psychology: impact of expressing emotional experiences on online content;[4]
- medicine: in medical research, medical treatment is an intervention whose effect are to be studied;
- marketing research: to analyze the effect of "designed market interventions" (e.g., advertising) on sales.[5]
- environmental sciences: impacts of human activities on environmental quality and ecosystem dynamics (e.g., forest logging on local climate).[6][7]
See also
[edit | edit source]References
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- ^ Handbook of Psychology, Research Methods in Psychology, p. 582
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