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Group-formation experiments, in which experimental units are randomlyassigned to groups, are a powerful tool for studying peer effects in the socialsciences. Existing design and analysis approaches allow researchers to drawinference from such experiments without relying on parametric assumptions. Inpractice, however, group-formation experiments are often coupled with a second,external intervention, that is not accounted for by standard nonparametricapproaches. This note shows how to construct Fisherian randomization tests andNeymanian asymptotic confidence intervals for such composite experiments,including in settings where the second intervention exhibits spillovers. Wealso propose an approach for designing optimal composite experiments.

Randomization Inference for Composite Experiments with Spillovers and Peer Effects