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集群随机试验的混合样本大小计算,使用保证.
S Faye Williamson1, Svetlana V Tishkovskaya2, Kevin J Wilson3
1Biostatistics Research Group, Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, UK.
确定集群试验的样本大小是复杂的. 贝叶斯保证提供了一种比传统功率计算更强大的方法,通过结合参数不确定性,导致更可靠的试验样本大小.
科学领域:
- 生物统计学 生物统计学
- 临床试验方法论 临床试验方法论
- 健康研究方法 卫生研究方法
背景情况:
- 集群随机试验 (CRT) 的样本大小确定具有挑战性,因为需要准确的集群内相关系数 (ICC) 估计.
- 传统的功率计算对ICC的不准确性很敏感,可能导致功率不足或过高的试验.
- 不准确的ICC估计通常来自对少数集群的研究,这复杂化了样本大小的规划.
研究的目的:
- 在CRT中提出混合贝叶斯保证和频率主义方法来确定样本大小.
- 将不确定性纳入关键参数,如ICC,标准偏差和集群大小变化系数.
- 通过使用CRT设计来证明中风后失禁的方法.
主要方法:
- 利用贝叶斯保证作为传统功率的替代品,并纳入关键参数的先前分布.
- 标准偏差,ICC和集群大小变化系数的指定先前分布.
- 将该方法应用于中风后失禁的CRT,并将结果与标准功率计算进行比较.
主要成果:
- 贝叶斯保证允许使用ICC的提取先前分布计算样本大小,而不是使用单点估计的功率计算.
- 建议的方法避免了样本大小的错误规范,当之前的分布有显著差异时,即使在类似的中位数.
- 考虑到所有干扰参数的不确定性,所需的样本大小没有大幅增加.
结论:
- 贝叶斯保证提高了对试验成功概率的理解,并提供了对参数不确定性的更强大的样本大小.
- 当难以获得可靠的参数估计时,这种方法特别有用.
- 混合方法为CRT中样本大小的确定提供了更可靠的替代方案.
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