样本大小和功率计算用于测试集群随机交叉设计中的治疗效果异质性
Xueqi Wang1,2, Xinyuan Chen3, Keith S Goldfeld4
1Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA.
Statistical methods in medical research
|May 1, 2024
概括
这项研究为集群随机交叉试验引入了新的样本大小公式,以检测患者亚群中的差异性治疗效应. 这些方法解释了不平等的集群大小,提高了相互作用测试的统计能力.
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:
- 集群随机交叉设计比平行臂设计提供了更好的效率.
- 现有的统计方法主要侧重于平均治疗效果,忽视子组变化.
- 了解跨患者亚群的治疗效果异质性变得越来越重要.
研究的目的:
- 开发样本大小公式,用于检测两种治疗,两期集群随机交叉试验中的治疗效果异质性.
- 将预先规定的患者亚群的相互作用测试纳入.
- 解决横截面和封闭队列抽样方案.
主要方法:
- 使用线性混合模型推导样本大小公式.
- 假设共变量和结果的模式相关性结构.
- 包括处理不平等集群大小的方法.
主要成果:
- 在集群随机交叉设计中进行相互作用测试的样本大小计算的新公式.
- 对不同集群大小对统计能力的影响的分析评估.
- 通过模拟和现实世界的试验应用方法的验证.
结论:
- 提出的方法为设计聚类随机交叉试验提供了一个强大的框架,重点是治疗效果异质性.
- 准确的样本大小确定对于检测亚群体中的差异性治疗效应至关重要.
- 这些公式有助于更好地了解不平等的集群大小如何影响研究能力.
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