What is a controlled interrupted time series design?
A controlled (or comparative) interrupted time series (CITS) involves adding a control series, which was not exposed to the intervention, to the basic ITS design (Figure 1). 9. This results in the definition of a more complex counterfactual based on both a before-after comparison and an intervention-control comparison.
What is the greatest threat to time series design?
Use of a control group addresses the greatest threat to the validity of a time series–design which is the occurrence of another event at the same time as the intervention, both of which may be associated with the outcome.
How is segmented regression analysis of interrupted time series used?
Segmented regression analysis is a powerful statistical method for estimating intervention effects in interrupted time series studies. In this paper, we show how segmented regression analysis can be used to evaluate policy and educational interventions intended to improve the quality of medication use and/or contain costs.
How are intercepts and slopes estimated in segmented regression?
In a basic segmented regression analysis [ 2 – 4 ], the time period is divided into pre- and post-intervention segments, and separate intercepts and slopes are estimated in each segment. Statistical tests of changes in intercepts and slopes pre- to post-intervention are carried out.
How is interrupted time series used in research?
Segmented regression analysis of interrupted time series studies in medication use research. Interrupted time series design is the strongest, quasi-experimental approach for evaluating longitudinal effects of interventions.
How is segmented regression used in a meta analytical model?
One approach is to conduct separate segmented regression analyses at each site, and then estimate the overall effect by pooling the estimates of intervention effect across sites using inverse variance weights in a meta-analytical model [ 11 ].