Chen Hsiang-Chun, Wehrly Thomas E
Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, U.S.A.
Stat Med. 2015 Feb 20;34(4):704-20. doi: 10.1002/sim.6374. Epub 2014 Nov 19.
The classic concordance correlation coefficient measures the agreement between two variables. In recent studies, concordance correlation coefficients have been generalized to deal with responses from a distribution from the exponential family using the univariate generalized linear mixed model. Multivariate data arise when responses on the same unit are measured repeatedly by several methods. The relationship among these responses is often of interest. In clustered mixed data, the correlation could be present between repeated measurements either within the same observer or between different methods on the same subjects. Indices for measuring such association are needed. This study proposes a series of indices, namely, intra-correlation, inter-correlation, and total correlation coefficients to measure the correlation under various circumstances in a multivariate generalized linear model, especially for joint modeling of clustered count and continuous outcomes. The proposed indices are natural extensions of the concordance correlation coefficient. We demonstrate the methodology with simulation studies. A case example of osteoarthritis study is provided to illustrate the use of these proposed indices.
经典一致性相关系数用于衡量两个变量之间的一致性。在最近的研究中，一致性相关系数已被推广，以使用单变量广义线性混合模型来处理指数族分布的响应。当对同一单位的响应通过几种方法进行重复测量时，就会出现多变量数据。这些响应之间的关系通常是人们感兴趣的。在聚类混合数据中，同一观察者内部的重复测量之间或同一受试者的不同方法之间可能存在相关性。需要用于测量这种关联的指标。本研究提出了一系列指标，即组内相关、组间相关和总相关系数，以测量多变量广义线性模型中各种情况下的相关性，特别是用于聚类计数和连续结果的联合建模。所提出的指标是一致性相关系数的自然扩展。我们通过模拟研究展示了该方法。提供了一个骨关节炎研究的案例示例来说明这些提出的指标的使用。
