设计单独随机的小组治疗试验,使用一般化估计方程重复测量结果
Xueqi Wang1,2, Elizabeth L Turner1,3, Fan Li2,4
1Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, North Carolina, USA.
Statistics in medicine
|November 27, 2023
概括
建议对具有纵向数据的个人随机组治疗 (IRGT) 试验进行样本大小计算. 这些方法,使用一般化的估计方程,准确地预测连续和二进制结果的研究功率.
科学领域:
- 生物统计学 生物统计学
- 公共卫生研究 公共卫生研究
- 临床试验设计 临床试验设计
背景情况:
- 个人随机组治疗 (IRGT) 试验在公共卫生中很常见.
- 这些试验往往涉及纵向数据,需要对样本大小进行计算,以考虑聚类和重复测量.
- 关于设计纵向IRGT试验的现有文献有限.
研究的目的:
- 为纵向IRGT试验提出样本大小计算程序.
- 为了解决连续和二进制结果.
- 在样本大小确定过程中考虑复杂的相关性结构.
主要方法:
- 使用了通用估计方程 (GEE) 方法.
- 使用区块可交换的关联结构,对处理和控制臂具有不同的参数.
- 调查了五种边际平均模型,包括时间恒定和时间变化的治疗效应.
主要成果:
- 为连续结果推导的闭式样本大小公式.
- 开发了对二进制结果的数值样本大小程序.
- 模拟证实,经验能力与预测能力密切匹配,即使只有八个组.
结论:
- 提出的基于GEE的样本大小程序对于纵向IRGT试验是有效的.
- 准确的样本大小计算对于使用IRGT的公共卫生研究中可靠的结果至关重要.
- 这些方法为设计复杂纵向研究的研究人员提供了宝贵的工具.
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