使用p值的总和进行可复制性的评估
Leonhard Held1, Samuel Pawel1, Charlotte Micheloud1
1Epidemiology Biostatistics and Prevention Institute (EBPI) and Center for Reproducible Science (CRS), University of Zurich, Hirschengraben 84, Zurich 8001, Switzerland.
Royal Society open science
|August 29, 2024
概括
这项研究引入了一种新方法,使用p值的和来评估科学可复制性. 它控制了I型错误,并允许成功复制,即使原始研究并不重要.
科学领域:
- 统计 统计 统计 统计
- 生物统计学 生物统计学
- 科学方法科学方法学
背景情况:
- 在药物开发中,使用原始和复制研究的统计学意义的"两次试验规则"在药物开发中很常见.
- 这一规则无法控制类型I错误率,当复制研究对非显著的原始发现进行时.
研究的目的:
- 提出一种替代方法来评估可复制性,使用两个研究中的p值的和.
- 开发一种控制整体I型错误率的方法,同时允许即使在非显著的原始结果中也实现复制成功.
主要方法:
- 提出一种基于原始和复制研究p值的总和的新方法.
- 校准方法以控制整体I型错误率.
- 将拟议的方法与两次试验规则,元分析和费舍尔的组合方法进行比较,使用来自四个大规模复制项目的数据.
主要成果:
- 拟议的p值总和方法控制了I型错误率,类似于两次试验规则.
- 该方法允许成功复制,即使原始研究的发现无关紧要.
- 一个未加权的版本可以将样本大小减少高达10%,因为当原始研究令人信服时,它需要更少的严格复制显著性.
- 减轻原始研究的权重可以解释偏差,需要更严格的复制标准和更大的样本大小.
结论:
- p值的总和为评估科学可重复性提供了一个灵活而强大的替代方案.
- 这种方法提高了复制评估的可靠性,特别是在没有重大初步发现的场景中.
- 这种方法对优化复制研究中的研究设计和样本大小具有实际意义.
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