Clip-OGD: An Experimental Design for Adaptive Neyman Allocation in Sequential Experiments
Clip-OGD:序贯实验中自适应 Neyman 分配的实验设计
From clinical development of cancer therapies to investigations into partisan bias, adaptive sequential designs have become increasingly popular method for causal inference, as they offer the possibility of improved precision over their non-adaptive counterparts. However, even in simple settings (e.g. two treatments) the extent to which adaptive designs can improve precision is not sufficiently well understood. In this work, we study the problem of Adaptive Neyman Allocation…