Robustness of Comparative Interrupted Time Series Designs in Practice

Much research in education is designed to address causal questions. By randomly assigning schools, classrooms, or students to treatment conditions, randomized controlled trials (RCTs) ensure that the treatment and control groups are equivalent in expectation, but RCTs are not always feasible to implement. When RCTs are not possible, education researchers rely on quasi-experimental research designs to address causal questions, but it is only appropriate to do so when these designs produce trustworthy estimates of causal effects. This project team examined the conditions under which comparative interrupted time series (CITS) study designs can yield trustworthy estimates of causal program effects. In addition, the research team for this project provided concrete guidance to education researchers using this study design as to the best procedures to follow in order to select comparison groups and modeling approaches.