Moyé L A
Department of Biometry, University of Texas School of Public Health, Houston 77030, USA.
Ann Epidemiol. 1998 Aug;8(6):351-7. doi: 10.1016/s1047-2797(98)00003-9.
Although much value has been placed on type I error event probabilities in clinical trials, interpretive difficulties often arise that are directly related to clinical trial complexity. Deviations of the trial execution from its protocol, the presence of multiple treatment arms, and the inclusion of multiple end points complicate the interpretation of an experiment's reported alpha level. The purpose of this manuscript is to formulate the discussion of P values (and power for studies showing no significant differences) on the basis of the event whose relative frequency they represent.
Experimental discordance (discrepancies between the protocol's directives and the experiment's execution) is linked to difficulty in alpha and beta interpretation. Mild experimental discordance leads to an acceptable adjustment for alpha or beta, while severe discordance results in their corruption.
Finally, guidelines are provided for allocating type I error among a collection of end points in a prospectively designed, randomized controlled clinical trial.
When considering secondary end point inclusion in clinical trials, investigators should increase the sample size to preserve the type I error rates at acceptable levels.
尽管在临床试验中I型错误事件概率备受重视，但常出现与临床试验复杂性直接相关的解释困难。试验执行与方案的偏差、多个治疗组的存在以及多个终点的纳入，使对实验报告的α水平的解释变得复杂。本文的目的是基于P值所代表的相对频率事件，对P值（以及显示无显著差异的研究的检验效能）展开讨论。
实验不一致性（方案指令与实验执行之间的差异）与α和β解释的困难相关。轻度的实验不一致性会导致对α或β进行可接受的调整，而严重的不一致性则会导致它们被破坏。
最后，为在前瞻性设计的随机对照临床试验的一系列终点中分配I型错误提供了指导原则。
在考虑将次要终点纳入临床试验时，研究者应增加样本量，以将I型错误率维持在可接受水平。
