用于评估与异质随机评分器和重复测量的定量数据一致性的统计模型
Claus Thorn Ekstrøm1, Bendix Carstensen2
1Section of Biostatistics, Department of Public Health, University of Copenhagen, Copenhagen, Denmark.
The international journal of biostatistics
|February 21, 2024
概括
本研究扩展了线性混合效应模型用于方法比较,量化随机测量方法之间的变化. 该方法增强了协议分析,超出了标准的Bland-Altman地块,用于各种应用.
科学领域:
- 生物统计学 生物统计学
- 统计建模 统计建模
- 方法比较研究 方法比较研究
背景情况:
- 传统的协议评估依赖于布兰德-阿尔特曼情节或对方法的协议限制.
- 情况出现时,测量方法是从一个更大的潜在方法群体中随机抽取的样本.
研究的目的:
- 扩展线性混合效应模型用于涉及随机测量方法的情况.
- 量化随机方法之间的变化,并将其纳入临床性能概括.
- 为了允许在模型中实现个别评分器精度和链接复制品.
主要方法:
- 扩展线性混合效应模型以适应随机测量方法.
- 整合了个别的评分器精度和链接的复制品.
- 在R.中使用MethComp包实现.
主要成果:
- 使用拟议的模型,对两个数据集估计一致性极限的演示.
- 应用到空间感知和消费者偏好数据.
- 量化方法间的变化作为一个额外的错误来源.
结论:
- 扩展模型为方法被认为是随机的方法进行方法比较提供了一个强大的框架.
- 这种方法通过考虑方法的可变性,可以更好地概括临床性能.
- "MethComp"软件包有助于应用这些先进的统计技术.
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