用集群数据和二进制结果进行单臂临床试验的样本大小计算
1Department of Optimization, Fraunhofer Institute for Industrial Mathematics, Kaiserslautern, Germany.
Biometrical journal. Biometrische Zeitschrift
|June 28, 2023
概括
这项研究通过应用Fleiss和Cuzick公式来简化对集群数据的样本大小计算. 它减少了定义假设和量化对治疗结果集群效应的复杂性.
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
- 流行病学 流行病学
背景情况:
- 样本大小计算对于可靠的临床试验结果至关重要.
- 在健康研究中常见的集群数据需要专门的统计方法.
- 集群二进制数据中样本大小的现有方法可能很复杂.
研究的目的:
- 为了简化对带有二进制结果的集群数据的样本大小计算.
- 应用Fleiss和Cuzick公式来估计类内相关系数.
- 为了减少在此类研究中确定样本大小的复杂性.
主要方法:
- 使用Fleiss和Cuzick (1979) 的公式来估计类内相关系数.
- 将这个公式应用于对聚类二进制数据的样本大小计算的特定环境.
- 专注于通过将其缩小到关键统计组件来简化计算过程.
主要成果:
- 证明了样本大小计算的复杂性显著降低.
- 表明该方法简化了定义虚假假设和替代假设的过程.
- 强调制定聚类对治疗成功概率的定量影响的重要性.
结论:
- 弗莱斯和库兹克公式提供了一种更容易使用的方法,用于在聚类二进制数据中计算样本大小.
- 这种方法提高了在临床和流行病学研究中确定样本大小的实用性.
- 通过采用这种简化方法,研究人员可以更有效地规划使用聚类二进制结果的研究.
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