功率分析用于修改的排名尺度的顺序分析,以及实用使用的在线和可下载工具
Hannah Johns1,2, Bruce Campbell2,3, Guillaume Turc4,5,6,7
1Melbourne Medical School, University of Melbourne, Victoria, Australia (H.J., L.C.).
Stroke
|June 2, 2023
概括
锦标赛方法准确计算顺序结果的功率,优于顺序后勤回归. 研究人员应该使用这些无假设的方法,并进行灵敏度分析,以确保可靠的研究设计.
科学领域:
- 统计 统计 统计 统计
- 临床试验 临床试验
- 健康研究方法 卫生研究方法
背景情况:
- 顺序结果,如修改的兰金度表,在临床研究中很常见.
- 对于顺序数据的现有功率分析方法缺乏系统的比较.
- 准确的功率分析对于有效的研究设计和样本大小估计至关重要.
研究的目的:
- 系统地比较功率分析方法的准确性和灵敏性,以获得顺序结果.
- 引入一个免费可用的在线工具,用于对顺序数据的功率和样本大小计算.
主要方法:
- 使用真实世界的临床试验数据 (AVERT,EXTEND,HERMES) 和均分布的模拟研究.
- 对正则后勤回归和各种锦标赛方法 (概括赔率比率,赢得概率,赢得比率,威尔科克森-曼-惠特尼U测试) 发表的功率公式的评估.
- 在线Shiny R应用程序的开发,用于功率和样本大小计算.
主要成果:
- 赛事方法的功率公式表现良好; 顺序逻辑回归公式是不准确的.
- 唐的Wilcoxon-Mann-Whitney U测试公式显示了最高的准确性.
- 所有方法都表现出类似的经验能力和对影响尺寸变化的敏感性.
结论:
- 没有假设的锦标赛方法样本大小公式准确计算功率,并推用于顺序结果.
- 对效应大小假设的敏感性分析对于样本大小估计至关重要.
- 开发的在线工具支持对顺序修改的排名表结果的功率分析.
相关概念视频
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