在横截面阶段子集群随机试验中评估调解
Zhiqiang Cao1, Fan Li2,3,4
1College of Big Data and Internet, Shenzhen Technology University, Shenzhen, P. R. China.
这项研究引入了新的回归方法,用于在随机化阶段集团随机化试验 (SW-CRTs) 中进行调解分析,并与相关数据相关联. 这些方法有助于理解治疗效果机制,即使是复杂的暴露时间变化.
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
- 流行病学 流行病学
背景情况:
- 调解分析对于理解治疗效果机制至关重要.
- 现有的方法对于阶段集群随机试验 (SW-CRTs) 中的相关数据是有限的.
- 了解SW-CRT中的调解对于公共卫生干预至关重要.
研究的目的:
- 开发和介绍基于回归的新方法,用于SW-CRT中介分析.
- 扩展调解分析以处理SW-CRT中常见的相关数据结构.
- 在复杂的SW-CRT设计中提供估计自然间接影响和调解比例的工具.
主要方法:
- 用线性和通用线性混合模型进行调解分析.
- 开发了自然间接效应和调解比例的估计器.
- 计算暴露时间治疗效应异质性的衍生中介表达式.
- 适用于连续和二进制调解器和结果的拟议方法.
主要成果:
- 开发的调解估计器在各种数据类型和治疗效果结构中表现良好.
- 这些方法在SW-CRT中成功处理相关数据.
- 对于典型和复杂的SW-CRT场景,具有时间变化的效果,都显示了有效性.
结论:
- 提出的基于回归的方法为SW-CRT中调解分析提供了强大的框架.
- 这些方法提高了对复杂试验设计中的治疗效果机制的理解.
- 附带的R包,调解SWCRT,有助于实际应用和实施.
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