Inference for Standard Trial Estimands after Data-Driven Subgroup Discovery
数据驱动亚组发现后标准试验估计量的推断
Data-driven subgroup identification is increasingly used in clinical trials, yet the effect reported for a discovered subgroup is typically the standard analysis: a Cox or generalized-linear-model treatment coefficient fitted within that subgroup. Selection by an effect-driven rule --- rewarding large estimated effects subject to screening and size criteria --- inflates the reported coefficient: a winner's curse invalidating naive intervals whether or not the identifier's…