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Stat Med. 2013 Sep 10;32(20):3436-48. doi: 10.1002/sim.5788. Epub 2013 Mar 31.

A method for processing multivariate data in medical studies.

Author information

1
The Neuropsychological Laboratory, CNS-Fed, 39 rue Meaux, 75019 Paris, France. olivier.coubard@cns-fed.com

Abstract

Traditional displays of principal component analyses lack readability to discriminate between putative clusters of variables or cases. Here, the author proposes a method that clusterizes and visualizes variables or cases through principal component analyses thus facilitating their analysis. The method displays pre-determined clusters of variables or cases as urchins that each has a soma (the average point) and spines (the individual variables or cases). Through three examples in the field of neuropsychology, the author illustrates how urchins help examine the modularity of cognitive tasks on the one hand and identify groups of healthy versus brain-damaged participants on the other hand. Some of the data used in this article were obtained from the Alzheimer's Disease Neuroimaging Initiative database. The urchin method was implemented in MATLAB, and the source code is available in the Supporting information. Urchins can be useful in biomedical studies to identify distinct phenomena at first glance, each having several measures (clusters of variables) or distinct groups of participants (clusters of cases).

KEYWORDS:

multivariate analysis; neuropsychology; principal component analysis; statistics

PMID:
23553725
PMCID:
PMC3744618
DOI:
10.1002/sim.5788
[Indexed for MEDLINE]
Free PMC Article
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