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样本大小计算用于比较两个选试验,当黄金标准随机缺失时
1Department of Epidemiology and Biostatistics, College of Public Health, University of South Florida, Tampa, Florida, USA.
Statistics in medicine
|May 15, 2024
概括
本研究引入了更简单的样本大小公式来比较诊断测试准确性,解决对设计中的验证偏差. 新的方法更容易使用,并产生与复杂的现有方法相似的结果.
科学领域:
- 生物统计学 生物统计学
- 医学诊断 医学诊断 医学诊断
- 临床试验 临床试验
背景情况:
- 比较诊断测试准确度至关重要,特别是在验证偏差的情况下.
- 对于配对设计的现有样本大小公式是复杂的,并且很难实现.
- 在评估诊断测试性能的研究中,配对设计是常见的.
研究的目的:
- 提出简化和直观的样本大小公式来比较两个灵敏度或特异性.
- 为配对设计提供现有复杂公式的实用替代方案,以提供具有验证偏差的复杂公式.
- 在样本大小计算中比较不同统计测试的效率.
主要方法:
- 为两个沃尔德试验和一个加权麦克纳马斯试验开发替代样本大小公式.
- 拟议公式与现有的复杂方法进行比较.
- 分析不同测试中的样本大小要求,考虑不一致和一致的对.
主要成果:
- 拟议的样本大小公式比现有的样本大小公式更简单,更直观.
- 所有三个考虑的测试 (两个沃尔德,一个加权的麦克纳马斯) 都导致类似的样本大小.
- 只有使用不一致对的权重麦克纳马尔测试,显示了与使用一致和不一致对的沃尔德测试相比较的样本大小需求.
结论:
- 简化样本大小计算现在可用于配对的诊断准确性研究,具有验证偏差.
- 选择的测试 (瓦尔德与加权的麦克纳马斯) 并不会显著影响样本大小要求.
- 这些发现有助于在诊断测试评估中更容易获得和更有效的研究设计.
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