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评估重复读数的内部、相互间以及总体一致性。

Assessing intra, inter and total agreement with replicated readings.

作者信息

Barnhart Huiman X, Song Jingli, Haber Michael J

机构信息

Department of Biostatistics and Bioinformatics, Duke Clinical Research Institute, Duke University, P.O. Box 17969, Durham, NC 27715, USA.

出版信息

Stat Med. 2005 May 15;24(9):1371-84. doi: 10.1002/sim.2006.

Abstract

In clinical studies, assessing agreement of multiple readings on the same subject plays an important role in the evaluation of continuous measurement scale. The multiple readings within a subject may be replicated readings by using the same method or/and readings by using several methods (e.g. different technologies or several raters). The traditional agreement data for a given subject often consist of either replicated readings from only one method or multiple readings from several methods where only one reading is taken from each of these methods. In the first case, only intra-method agreement can be evaluated. In the second case, traditional agreement indices such as intra-class correlation (ICC) or concordance correlation coefficient (CCC) is often reported as inter-method agreement. We argue that these indices are in fact measures of total agreement that contains both inter and intra agreement. Only if there are replicated readings from several methods for a given subject, then one can assess intra, inter and total agreement simultaneously. In this paper, we present new inter-method agreement index, inter-CCC, and total agreement index, total-CCC, for agreement data with replicated readings from several methods where the ICCs within methods are used to assess intra-method agreement for each of the several methods. The relationship of the total-CCC with the inter-CCC and the ICCs is investigated. We propose a generalized estimating equations approach for estimation and inference. Simulation studies are conducted to assess the performance of the proposed approach and data from a carotid stenosis screening study is used for illustration.

摘要

在临床研究中,评估同一受试者多次测量结果的一致性在连续测量量表的评估中起着重要作用。受试者内部的多次测量可能是使用相同方法的重复测量结果,或/和使用几种方法(如不同技术或多个评分者)的测量结果。对于给定受试者的传统一致性数据通常要么仅由一种方法的重复测量结果组成,要么由几种方法的多次测量结果组成,而这些方法中的每种方法仅获取一次测量结果。在第一种情况下,只能评估方法内部的一致性。在第二种情况下,传统的一致性指标,如组内相关系数(ICC)或一致性相关系数(CCC),通常被报告为方法间的一致性。我们认为这些指标实际上是总一致性的度量,其中包含方法间和方法内的一致性。只有当给定受试者有几种方法的重复测量结果时,才能同时评估方法内、方法间和总一致性。在本文中,我们针对具有几种方法的重复测量结果的一致性数据,提出了新的方法间一致性指标——方法间CCC和总一致性指标——总CCC,其中方法内的ICC用于评估几种方法中每种方法的方法内部一致性。研究了总CCC与方法间CCC及ICC之间的关系。我们提出了一种广义估计方程方法用于估计和推断。进行了模拟研究以评估所提出方法的性能,并使用颈动脉狭窄筛查研究的数据进行说明。

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