重新思考成功的概率作为贝叶斯的实用工具
Fulvio De Santis1, Stefania Gubbiotti1, Francesco Mariani1
1Department of Statistical Sciences, Sapienza University of Rome, Rome, Italy.
Biometrical journal. Biometrische Zeitschrift
|July 15, 2025
概括
本研究引入了一种新的决策理论方法,用于定义混合频率-贝叶斯试验中的成功概率 (PoS). 拟议的基于实用性的PoS (u-PoS) 提供了概念上的优势,并且可以导致更小的最佳样本大小.
科学领域:
- 生物统计学 生物统计学
- 临床试验设计 临床试验设计
- 决策理论 决策理论
背景情况:
- 现有的混合频率主义-贝叶斯式方法使用传统的功率函数来定义成功概率 (PoS).
- 这些定义并不单一,存在潜在的缺点.
- 目前的方法集中在拒绝零假设,而不是选择正确的假设.
研究的目的:
- 提出一个统一的,决策理论的方法来定义PoS.
- 引入基于预期效用 (u-PoS) 的PoS新定义.
- 与现有方法相比,评估概念优势和对样本大小的影响.
主要方法:
- 开发了混合频率学-贝叶斯试验的决策理论框架.
- 定义了一个新的PoS指标,即试验的预期效用 (u-PoS).
- 分析了u-PoS的属性,包括它与样本大小的关系.
主要成果:
- 拟议的u-PoS被定义为在零假设和替代假设之间做出正确选择的预期概率.
- 这种方法比现有的PoS定义提供了概念上的改进.
- 最佳的样本大小在设计前期为零假设赋予正概率时会减少.
结论:
- 决策理论方法在混合试验中提供了一个更强大的PoS定义.
- u-PoS指标更好地与选择正确假设的目标保持一致.
- 这种框架可以带来更高效的临床试验设计,样本规模更小.
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