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用于量化两个变量之间一致性的绝对差异统计量。

-statistics of absolute differences for quantifying the agreement between two variables.

作者信息

Tashakor Elahe, Chinchilli Vernon M

机构信息

a Department of Public Health Sciences , Penn State College of Medicine , Hershey , PA , USA.

出版信息

J Biopharm Stat. 2019;29(1):174-188. doi: 10.1080/10543406.2018.1489406. Epub 2018 Jun 28.

Abstract

In many clinical studies, Lin's (1989) concordance correlation coefficient (CCC) is a popular measure of agreement for continuous outcomes. Most commonly, it is used under the assumption that data are normally distributed. However, in many practical applications, data are often skewed and/or thick-tailed. King and Chinchilli (2001) proposed robust estimation methods of alternative CCC indices, and we propose an approach that extends the existing methods of robust estimators by focusing on functionals that yield robust -statistics. We provide two data examples to illustrate the methodology, and we discuss the results of computer simulation studies that evaluate statistical performance.

摘要

在许多临床研究中,林(1989年)提出的一致性相关系数(CCC)是用于衡量连续结果一致性的常用指标。最常见的是,它在数据呈正态分布的假设下使用。然而,在许多实际应用中,数据往往是偏态的和/或厚尾的。金和钦奇利(2001年)提出了替代CCC指数的稳健估计方法,我们提出了一种方法,通过关注能产生稳健统计量的泛函来扩展现有稳健估计量的方法。我们提供了两个数据示例来说明该方法,并讨论了评估统计性能的计算机模拟研究结果。

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