CoPlot: A tool for visualizing multivariate data in medicine
CoPlot: A tool for visualizing multivariate data in medicine
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DOI：
10.1002/sim.3078
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发表时间：
2008-05-30
影响因子：
2
通讯作者：
Raveh, Adi
中科院分区：
文献类型：
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作者：
Bravata, Dena M.;Shojania, Kaveh G.;Raveh, Adi
医学中的许多关键问题需要分析复杂的多变量数据，这些数据通常来自描述众多受试者的众多变量的大型数据集。在本文中，我们描述了CoPlot，一种用于可视化医学中多变量数据的工具。CoPlot是多维标度（MDS）的一种改编，它解决了MDS的几个关键限制，即MDS地图不允许同时可视化观测和变量，并且MDS地图上的轴没有固有的意义。通过解决这些问题，CoPlot促进了多元数据的丰富解释。我们在最近发布的系统性综述数据集上使用CoPlot展示了一个示例，该数据集描述了炭疽儿童的临床特征和疾病进展，并提供了使用CoPlot评估和解释其他医疗保健数据集的建议。版权所有（C）2007约翰威利父子有限公司
Many critical questions in medicine require the analysis of complex multivariate data, often from large data sets describing numerous variables for numerous subjects. In this paper, we describe CoPlot, a tool for visualizing multivariate data in medicine. CoPlot is an adaptation of multidimensional scaling (MDS) that addresses several key limitations of MDS, namely that MDS maps do not allow for visualization of both observations and variables simultaneously and that the axes on an MDS map have no inherent meaning. By addressing these issues, CoPlot facilitates rich interpretation of multivariate data. We present an example using CoPlot on a recently published data set from a systematic review describing clinical features and disease progression of children with anthrax and provide recommendations for the use of CoPlot for evaluating and interpreting other healthcare data sets. Copyright (C) 2007 John Wiley & Sons, Ltd.