An important pursuit by a body of criminological research is its endeavor to determine whether interventions or policy changes effectively achieve their intended goals. Because theories predict that interventions could either improve or worsen outcomes, estimators designed to improve the accuracy of identifying program or policy effects are in demand. This article introduces the series hazard model as an alternative to interrupted time series when testing for the effects of an intervention on event-based outcomes. It compares the two approaches through an example that examines the effects of two interventions on aerial hijacking. While series hazard modeling may not be appropriate for all event-based time series data or every context, it is a robust alternative that allows for greater flexibility in many contexts. (Published Abstract)