论文标题
P值窥视和估计极值
p-value peeking and estimating extrema
论文作者
论文摘要
统计假设检验中的一个普遍问题是，报告的$ p $值受到数据“窥视”的偏见 - 随着收集更多的数据样本，仅报告测试统计量的极端值的做法。我们开发了有原则的机制来估计测试统计的超级超值，该机制直接解决了在某些一般情况下窥视的效果。
A pervasive issue in statistical hypothesis testing is that the reported $p$-values are biased downward by data "peeking" -- the practice of reporting only progressively extreme values of the test statistic as more data samples are collected. We develop principled mechanisms to estimate such running extrema of test statistics, which directly address the effect of peeking in some general scenarios.
