概括
在随机临床试验 (RCT) 中降低p值值会增加假负结果,可能会隐藏有效的治疗方法. 灵活的门提供了最小的误差,但需要后期数据以获得准确性,这表明像贝叶斯分析这样的替代统计方法可能更适合于RCT.
科学领域:
- 临床研究中的统计方法.
- 基于证据的医学和临床实践.
背景情况:
- 随机临床试验 (RCT) 是临床实践的基础.
- 有关RCT结果的可复制性是一个问题,有些人将其归因于严格的p值值.
- 降低显著性值可能会降低研究能力并增加虚假负面.
研究的目的:
- 评估不同p值显著性值对RCT结果的影响.
- 评估虚假阳性和虚假阴性利率之间的权衡,使用不同的门.
- 探索灵活的p值值在RCT的统计推断中的实用性.
主要方法:
- 从Cochrane系统审查数据库 (CDSR) 重新分析了22,500个RCT.
- 应用了固定的p值值 (0.05和0.005) 和一个新的灵活值.
- 灵活的门旨在尽量减少统计推断错误的加权总和.
主要成果:
- 使用p < 0.05,有28.5%的RCT是显著的;p < 0.005产生了14.2%;灵活值导致9.9%.
- 在p<0.05时显著的RCT中,有相当一部分 (2/3) 在灵活值时不显著.
- 降低p值减少了假阳性,但增加了假阴性 (功率下降),冒着发现重要的治疗方法的风险.
结论:
- 由于假负率的增加,降低p值值是不建议的.
- 灵活的门可以最大限度地减少推断错误,但需要先验估计,限制精度.
- 频率主义框架存在固有的冲突;贝叶斯方法可能为RCT数据分析提供更合适的替代方案.
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