发表机构
University of Sydney; Tufts University（悉尼大学; 塔夫茨大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究探讨阈值选择中的决策噪声对所选群体平均真实值的影响，发现固定阈值时噪声增大可提高所选平均值，还指出治疗选择中噪声能产生亚组收益差异。
AI 中文摘要
更嘈杂的阈值选择能否产生具有更高平均真实值的群体？我们通过改变固定评估误差的尺度来回答该问题。在选择率固定的情况下，噪声越小会产生一阶随机占优的所选值分布；但在固定阈值时，即使以真实值与阈值的距离加权选择错误的选择损失会增加，更大的噪声仍可提高所选平均值。在联合高斯分布下，我们刻画了所选平均值随噪声上升或下降的情况。在治疗选择中，尽管总体收益分布相同，仅噪声就能在参与者的平均收益中产生亚组差异。
英文摘要
Can noisier threshold selection produce a group with higher mean true value? We answer this question by varying the scale of a fixed assessment error. Holding the selection rate fixed, less noise yields a first-order stochastically dominant distribution of selected values. At a fixed threshold, however, more noise can raise the selected mean even as selection loss, which weights selection mistakes by the distance of true value from the threshold, increases. Under joint Gaussianity, we characterize when the selected mean rises or falls with noise. In treatment selection, noise alone can generate subgroup differences in participants' average gains despite identical population gain distributions.
