Code and data for project: Time aggregation in interrupted time series can introduce bias in immediate level change effect estimates when using segmented linear regression. Pre-publication version.

When aggregating ITS data over time, researchers need to be aware of the potential for bias in the estimate of the immediate level change parameter, so that they can mitigate its impact. The commonly used "immediate" level change parameter is not always calculated at the designated time, nor described appropriately. The code contained in this repository includes a simulation and example of this effect. The version attached here is pre-publication.