复习样本大小确定方法在变异模型的单向分析中的类内相关系数
Dipro Mondal1, Sophie Vanbelle1, Alberto Cassese2
1Faculty of Health Medicine and Life Sciences, Department of Methodology and Statistics, Care and Public Health Research Institute (CAPHRI), Maastricht University, Limburg, The Netherlands.
Statistical methods in medical research
|February 6, 2024
概括
确定可靠性研究的样本大小至关重要. 这项研究比较了类内相关系数 (ICC) 置信区间方法,并提供了样本大小计算的一般程序,有助于研究规划.
科学领域:
- 统计 统计 统计 统计
- 生物统计学 生物统计学
- 测量科学 测量科学 测量科学
背景情况:
- 定量测量仪器的可靠性通常使用类内相关系数 (ICC) 来评估.
- ICC计算依赖于单向差异分析 (ANOVA) 模型,当参与者被不同评分器测量一次或被单个评分器/设备测量多次时.
- 准确的样本大小确定对于规划强大的可靠性研究至关重要.
研究的目的:
- 为了比较各种可信度区间 (CI) 方法的统计特性,包括那些以前没有研究过的方法.
- 开发使用单向ANOVA模型进行可靠性研究的一般样本大小确定程序,以适应缺乏封闭式公式的情况.
- 为可靠性研究设计选择适当的样本大小确定方法提供指导.
主要方法:
- 系统性文献审查以确定基于CI的ICC样本大小确定方法.
- 对ICC.不同CI方法的统计性能进行比较分析.
- 在R Shiny应用程序中开发和实施一般样本大小确定程序.
主要成果:
- 根据ICC的置信区间确定了三种主要样本大小确定方法.
- 评估了八种不同的CI方法的统计特性,突出了常用的WaldCI的局限性.
- 开发了一种适用于各种CI方法的样本大小计算的灵活程序.
结论:
- 信任区间方法的选择显著影响了ICC研究中样本大小估计的可靠性.
- 提供了通用程序和R Shiny应用程序,以促进可靠性研究中的知情样本大小决策.
- 建议研究人员根据不同ICC置信区间的属性仔细选择样本大小确定方法.
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