联合镜像程序:控制识别同时信号的错误发现率
Linsui Deng1,2, Kejun He2, Xianyang Zhang3
1School of Data Science, The Chinese University of Hong Kong, Shenzhen 518172, China.
Biometrics
|December 13, 2024
概括
本研究引入了联合镜子 (JM) 程序,用于同时测试多个假设. 联合管理程序有效地控制了复合虚假发现率 (cFDR),并在各种场景中提高了统计能力.
科学领域:
- 统计方法学的统计方法.
- 假设测试 测试 假设测试
- 数据分析数据分析
背景情况:
- 识别特定特征通常需要测试多个假设以获得联合统计学意义.
- 应用包括调解和可复制性分析,这些分析同时检查多个效应或信号.
研究的目的:
- 提出一种新的联合镜子 (JM) 程序,通过联合假设测试来检测感兴趣的特征.
- 控制错误发现率 (FDR) 并引入更严格的复合FDR (cFDR) 措施.
- 增强检测重要特征的统计能力.
主要方法:
- JM程序使用代收缩方法来控制错误发现比例.
- 采用一个留下一项的技术来证明在有限样本中的cFDR控制.
- 提出了一种高效的算法来实施JM程序,以适应部分订单.
主要成果:
- 在有限的样本中,JM程序有效控制了复合FRD (cFDR).
- 模拟显示了在各种场景中增强的统计能力,包括依赖测试统计数据.
- 该方法在现实世界的调解和可复制性分析中被证明是有用的.
结论:
- 联合镜子 (JM) 程序为联合假设测试提供了一个强大的方法.
- 与现有方法相比,它提供了有效的FDR控制和更好的统计能力.
- 联合测量程序适用于生物统计学和遗传学等领域的复杂现实数据分析.
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