Pfizer Inc., Collegeville, PA, 19426, U.S.A.
Stat Med. 2013 May 10;32(10):1730-8. doi: 10.1002/sim.5488. Epub 2012 Jul 16.
This paper proposes a multiple testing procedure that allows one to reject each individual hypothesis at a prespecified level α, while still controlling the familywise error rate at α in the strong sense. Typically, rejecting a hypothesis when its marginal p-value is ≤ α in a multiple hypothesis testing setting will lead to an inflation of familywise error rate. However, this inflation can be avoided if a particular consistency criterion is prespecified and incorporated in the testing algorithm. The criterion is equivalent to requiring that all p-values be smaller than or equal to a particular threshold in the one-sided hypothesis testing setting. Extensions to the two-sided hypothesis testing setting and extensions to situations where the criterion can be chosen per user's preference are also presented.
本文提出了一种多重检验程序,允许在预设水平α下拒绝每个个体假设,同时在强意义上控制家族错误率为α。通常,在多重假设检验中,当边际 p 值≤α时拒绝一个假设会导致家族错误率膨胀。然而,如果预设并将特定一致性准则纳入检验算法,则可以避免这种膨胀。该准则等效于要求所有 p 值在单侧假设检验设置中均小于或等于特定阈值。还提出了对双边假设检验设置的扩展以及可以根据用户偏好选择准则的情况的扩展。