Multi-Armed RCTs: A Design-Based Framework
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Multi-armed designs are becoming increasingly common in social policy research to simultaneously examine the effects of multiple interventions in a single study. This report describes how design-based estimators for the two-group design need to be modified for the multi-armed design when comparing pairs of research groups to each other. It also discusses multiple comparison adjustments when conducting hypothesis tests across pairwise contrasts to identify the most effective interventions. Finally, it discusses the complex assumptions required to identify and estimate the complier average causal effect (CACE) parameter in the multi-armed context.
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