重复纳入集群随机试验:用于评估群体级干预措施的新类设计
Jessica Kasza1, Kelsey L Grantham1, Rhys Bowden1
1School of Public Health and Preventive Medicine, Monash University, Melbourne 3004, Australia.
Biometrics
|February 11, 2026
概括
这项研究引入了重复纳入集群随机试验,允许集群在同一试验中重新随机化. 这种设计可以保持或增加统计能力,同时可能减少对新集群招聘的需求.
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:
- 个别随机试验允许多个参与者被包含在独立的随机化中,增强招募.
- 重新随机化设计增加了试验招募率,但需要额外的假设来精确估计治疗效果.
研究的目的:
- 引入一个新的类型的集群随机试验设计:重复纳入集群随机试验.
- 评估同一个试验中重新随机集群的潜力,以提高效率和功率.
主要方法:
- 建议在单个试验中对集群进行串行随机化,以适应标准或纵向设计 (例如交叉).
- 在假设在重复的集群包含中保持恒定的处理效果的情况下分析功率.
- 将功率与具有相当总量测量的传统设计进行比较,但没有集群重新随机化.
主要成果:
- 重复纳入集群随机试验可以达到相同的或更高的统计能力,而非重新随机试验的测量总数相同.
- 维持或增加功率取决于具体的研究设计和集群内相关结构.
- 越来越多的集群内部比较提高了研究能力.
结论:
- 重复纳入集群随机试验提供了一个可行的策略,以减少招聘新集群的负担,特别是当招聘具有挑战性时.
- 这种设计可以保持或提高统计能力,使试验更有效率.
- 设计的选择和考虑集群内部的相关性对于优化功率至关重要.
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