Evaluation of statistical methods used in the analysis of interrupted time series studies: a simulation study

Abstract

Background: Interrupted time series (ITS) studies are frequently used to evaluate the effects of population-level interventions or exposures. However, examination of the performance of statistical methods for this design has received relatively little attention. Methods: We simulated continuous data to compare the performance of a set of statistical methods under a range of scenarios which included different level and slope changes, varying lengths of series and magnitudes of lag-1 autocorrelation. We also examined the performance of the Durbin-Watson (DW) test for detecting autocorrelation. Results: All methods yielded unbiased estimates of the level and slope changes over all scenarios. Th..