Literature DB >> 17972340

CoPlot: a tool for visualizing multivariate data in medicine.

Dena M Bravata1, Kaveh G Shojania, Ingram Olkin, Adi Raveh.   

Abstract

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.

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Year:  2008        PMID: 17972340     DOI: 10.1002/sim.3078

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  4 in total

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Journal:  Arthritis Res Ther       Date:  2010-04-27       Impact factor: 5.156

2.  Consensus-based recommendations for investigating clinical heterogeneity in systematic reviews.

Authors:  Joel J Gagnier; Hal Morgenstern; Doug G Altman; Jesse Berlin; Stephanie Chang; Peter McCulloch; Xin Sun; David Moher
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3.  Experts' perceptions on the use of visual analytics for complex mental healthcare planning: an exploratory study.

Authors:  Erin I Walsh; Younjin Chung; Nicolas Cherbuin; Luis Salvador-Carulla
Journal:  BMC Med Res Methodol       Date:  2020-05-07       Impact factor: 4.615

Review 4.  Investigating clinical heterogeneity in systematic reviews: a methodologic review of guidance in the literature.

Authors:  Joel J Gagnier; David Moher; Heather Boon; Joseph Beyene; Claire Bombardier
Journal:  BMC Med Res Methodol       Date:  2012-07-30       Impact factor: 4.615

  4 in total

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