Staggered Rollout Designs Enable Causal Inference Under Interference Without Network Knowledge
无需网络知识的干扰下因果推断:分阶段随机推广设计
Randomized experiments are widely used to estimate causal effects across a variety of domains. However, classical causal inference approaches rely on critical independence assumptions that are violated by network interference, when the treatment of one individual influences the outcomes of others. All existing approaches require at least approximate knowledge of the network, which may be unavailable and costly to collect. We consider the task of estimating the total…