LATEBREAKER
Study Design
Staggered interventions with no control groups Brice Batomen* Brice Batomen Tarik Benmarhnia
The limitations of the two-way fixed effects for the impact evaluation of interventions occurring at different times for each group, ‘staggered interventions’ have been highlighted in the last decade in the econometric literature and, more recently, in epidemiological research. Although many alternative strategies (staggered difference-in-differences, generalized synthetic control method, etc..) have been proposed, the focus has predominantly been on scenarios where one or more control groups are available. However, control groups are often unavailable, due to limitations in the available data or because all units have received the intervention. In such context, interrupted time series (ITS) designs can be applied. The extent to which common model specifications for ITS analyses are limited in the case of staggered interventions remains an underexplored area in the methodological literature. In this work, we aim to demonstrate that standard ITS model specifications typically yield biased results for staggered interventions, and we propose alternative model specifications inspired by recent developments in the difference-in-differences literature to propose adapted analytical strategies.