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Interrupted time series analysis is a quasi-experimental design that can evaluate an intervention effect, using longitudinal data. The advantages, disadvantages, and underlying assumptions of various modelling approaches are discussed using published examples Summary points Interrupted time series analysis is arguably the “next best” approach for dealing with interventions when randomisation is not possible or clinical trial data are not available Although several assumptions need to be satisfied first, this quasi-experimental design can be useful in providing answers about population level interventions and effects However, their implementation can be challenging, particularly for non-statisticians

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