A method for processing multivariate data in medical studies.
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 meth...
| Publicado en: | Statistics in Medicine Vol. 32; no. 20; pp. 3436 - 3449 |
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| Autor principal: | |
| Formato: | research Journal Article |
| Publicado: |
Wiley-Blackwell
Sep2013
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=104088164&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104088164 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 02776715 2DZ jtl: Statistics in Medicine issn: 02776715 maglogo: Y pubinfo: dt: Sep2013 vid: 32 iid: 20 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 104088164 NLM23553725 2012226450 10.1002/sim.5788 NLM23553725 PMC3744618 104088164 ppf: 3436 ppct: 13 formats: tig: atl: A method for processing multivariate data in medical studies. aug: au: Coubard, Olivier A affil: The Neuropsychological Laboratory, CNS-Fed, 39 rue Meaux, 75019 Paris, France. olivier.coubard@cns-fed.com sug: subj: Data Analysis, Statistical Multivariate Analysis Alzheimer's Disease Pathology Cluster Analysis Neuroradiography Methods Neuroradiography Standards Factor Analysis Study Design ab: 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). pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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