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Cluster and Multiple Correspondence Analyses in Rheumatology: Paths to Uncovering Relationships in a Sea of Data
Lu Han1, Susanne M Benseler2, Pascal N Tyrrell3
1Department of Medical Imaging, University of Toronto, 263 McCaul Street, Toronto, Ontario M5T 1W7, Canada.
Abstract:
Rheumatic diseases encompass a wide range of conditions caused by inflammation and dysregulation of the immune system resulting in organ damage. Research in these heterogeneous diseases benefits from multivariate methods. The aim of this review was to describe and evaluate current literature in rheumatology regarding cluster analysis and correspondence analysis. A systematic review showed an increase in studies making use of these 2 methods. However, standardization in how these methods are applied and reported is needed. Researcher expertise was determined to be the main barrier to considering these approaches, whereas education and collaborating with a biostatistician were suggested ways forward.
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