在多中心随机对照试验中计算中心级效应.
Shofiqul Islam1, Shrikant I Bangdiwala2,3
1Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Canada. shofiqul.islam@phri.ca.
Trials
|June 17, 2024
概括
分析多中心随机对照试验 (RCT) 需要仔细考虑中心效应. 将这些效应视为固定的或随机的会影响假设测试和试验分析中的错误率.
科学领域:
- 临床试验方法论 临床试验方法论
- 生物统计学 生物统计学
- 医疗保健服务研究 医疗服务研究
背景情况:
- 多中心随机对照试验 (RCT) 提高了招聘速度和人口通用性.
- 参与者特征,现场实践和调查人员专业知识的异质性在各中心之间可能导致影响估计的变化.
- 标准分析经常忽略中心效应,但它们对初级假设测试的影响尚不清楚.
研究的目的:
- 审查目前在已发表的RCT中计算中心效应的实践.
- 研究不同分析方法 (忽略,固定效应,随机效应) 对多中心RCT中假设测试的影响.
- 根据它们对统计能力和错误率的影响,提供关于何时考虑中心效应的建议.
主要方法:
- 审查已发表的多中心RCT分析,以评估有关中心效应的当前做法.
- 模拟研究使用线性和逻辑回归模型,分别用于连续和二进制结果.
- 三种方法的比较:忽略中心效应,将中心视为固定效应,将中心视为随机效应.
- 评估这些方法对I型和II型错误率的影响.
主要成果:
- 在多中心RCT中,通常在各中心之间观察到影响估计的显著异质性.
- 分析方法的选择 (忽略,固定或随机效应) 影响了I型和II型错误率.
- 模拟结果表明,对中心效应的计算可能会影响初级假设测试的有效性.
结论:
- 在多中心RCT中忽视中心效应可能导致关于治疗疗效的不准确结论.
- 计算中心效应,无论是固定效应还是随机效应,对于保持假设测试的完整性至关重要.
- 提供了指导方针,以帮助研究人员确定何时中心级影响需要特定的分析调整.
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