Revisiting the concept of a symmetric index of agreement for continuous datasets.
Revisiting the concept of a symmetric index of agreement for continuous datasets.
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DOI：
10.1038/srep19401
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发表时间：
2016-01-14
影响因子：
4.6
通讯作者：
Meroni M
中科院分区：
文献类型：
--
作者：
Duveiller G;Fasbender D;Meroni M
在科学研究中，量化两个数据集之间的接近程度是一项常见且必要的工作。皮尔逊积矩相关系数r是一种广泛使用的测量两个数据序列之间线性依赖程度的方法，但它不能表明这些序列的值在量级上有多相似。虽然已经提出了许多索引来比较数据集和参考，但只有很少的索引可用于比较具有相同（或未知）可靠性的两个数据集。在对为完成这项任务而设计的指标进行简要回顾和数值测试之后，本文展示了Mielke提出的指标如何在稍加修改后满足一系列期望的性质，即无维、有界、对称、易于计算和对r的直接解释。因此，我们表明该指标可以被认为是对r的自然扩展，根据分析数据集之间的偏差降低r的值。本文还提出了一种基于特征分解的有效方法来理清对该协议的系统贡献和非系统贡献。并在综合数据集和实际数据集上说明了该指数的使用和价值。
Quantifying how close two datasets are to each other is a common and necessary undertaking in scientific research. The Pearson product-moment correlation coefficient r is a widely used measure of the degree of linear dependence between two data series, but it gives no indication of how similar the values of these series are in magnitude. Although a number of indexes have been proposed to compare a dataset with a reference, only few are available to compare two datasets of equivalent (or unknown) reliability. After a brief review and numerical tests of the metrics designed to accomplish this task, this paper shows how an index proposed by Mielke can, with a minor modification, satisfy a series of desired properties, namely to be adimensional, bounded, symmetric, easy to compute and directly interpretable with respect to r. We thus show that this index can be considered as a natural extension to r that downregulates the value of r according to the bias between analysed datasets. The paper also proposes an effective way to disentangle the systematic and the unsystematic contribution to this agreement based on eigen decompositions. The use and value of the index is also illustrated on synthetic and real datasets.