Department of Epidemiology and Biostatistics, Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada.
Robarts Research Institute, Western University, London, Ontario, Canada.
J Biopharm Stat. 2022 Sep 3;32(5):740-767. doi: 10.1080/10543406.2022.2030747. Epub 2022 Feb 25.
Concordance refers to the probability that subjects with high values on one variable also have high values on another variable. This index has wide application in practice, as a measure of effect size in group-comparison studies, an index of accuracy in diagnostic studies, and a discrimination index for prediction models. Herein, we provide a unified framework for statistical inference involving concordance indices for standard variables of binary, ordinal, and continuous types. In particular, we develop confidence interval procedures for a single concordance index and differences between two correlated indices. Simulation results show that procedures based on logit-transformation for a single index and Fisher’s z-transformation for a difference between indices perform very well in terms of coverage and tail errors even when the sample size is as small as 30, unless the concordance is high and the standard is a binary variable for which at least 50 subjects are needed. We illustrate the procedures for a variety of standard variables with previously published data. Illustrative SAS code is provided.
一致性是指在一个变量上具有高值的对象在另一个变量上也具有高值的概率。该指标在实践中有广泛的应用，可作为组间比较研究中效应大小的度量指标、诊断研究中的准确性指标以及预测模型的区分指标。在此，我们提供了一个统一的框架，用于对标准的二分类、有序分类和连续型变量的一致性指标进行统计推断。具体而言，我们为单个一致性指标和两个相关指标之间的差异开发了置信区间程序。模拟结果表明，基于单个指标的对数变换和基于指标之间差异的 Fisher’s z 变换的程序在覆盖范围和尾部误差方面表现非常好，即使样本量小至 30，除非一致性高且标准为二分类变量，此时至少需要 50 个对象。我们用以前发表的数据说明了各种标准变量的程序。提供了说明性的 SAS 代码。
