The use of multiple correspondence analysis to explore associations between categories of qualitative variables in healthy ageing

Detalhes bibliográficos
Autor(a) principal: Costa, Patrício Soares
Data de Publicação: 2013
Outros Autores: Santos, Nadine Correia, Cunha, Pedro, Cotter, Jorge, Sousa, Nuno
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/1822/25613
Resumo: In press
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spelling The use of multiple correspondence analysis to explore associations between categories of qualitative variables in healthy ageingPerceptual mapsCognitionNeurocognitive assessmentClinical variablesLifestyleAgeingIn pressPopulation studies are often characterized by a plethora of data that includes quantitative to qualitative variables. The main focus of this study was to illustrate the applicability of multiple correspondence analysis (MCA) in detecting and representing underlying structures in large datasets used to investigate cognitive ageing. Principal component analysis (PCA) was used to obtain main cognitive dimensions (based on the continuous neurocognitive test variables) and MCA to detect and explore relationships of cognitive, clinical, physical and lifestyle categorical variables across the low-dimensional space. Altogether the technique allows to not only simplify complex data, providing a detailed description of the data and yielding a simple and exhaustive analysis, but also to handle a large and diverse dataset comprised of quantitative, qualitative, objective and subjective data. Two PCA dimensions were identified (general cognition/executive function and memory) and two main MCA dimensions were retained. As expected, poorer cognitive performance was associated with older age, less school years, unhealthier lifestyle indicators and presence of pathology. Interestingly, the first MCA dimension indicated the clustering of general/executive function and lifestyle indicators and education, while the second association between memory and clinical parameters and age. The clustering analysis with object scores method was used to identify groups sharing similar characteristics within each of the identified dimensions. Following MCA findings, the weaker cognitive clusters in terms of memory and executive function comprised individuals with characteristics contributing to a higher MCA dimensional mean score (age, less education and presence of indicators of unhealthier lifestyle habits and/or clinical pathologies). MCA provided a powerful tool to explore complex ageing data, covering multiple and diverse variables, showing not only if a relationship exists between variables but also how they are related, offering at the same time statistical results can be seen both analytically and visually.EC -European CommissionHindawi Publishing CorporationUniversidade do MinhoCosta, Patrício SoaresSantos, Nadine CorreiaCunha, PedroCotter, JorgeSousa, Nuno2013-10-092013-10-09T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/1822/25613eng2090-221210.1155/2013/302163http://www.hindawi.com/info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-21T12:42:27Zoai:repositorium.sdum.uminho.pt:1822/25613Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T19:39:41.363575Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv The use of multiple correspondence analysis to explore associations between categories of qualitative variables in healthy ageing
title The use of multiple correspondence analysis to explore associations between categories of qualitative variables in healthy ageing
spellingShingle The use of multiple correspondence analysis to explore associations between categories of qualitative variables in healthy ageing
Costa, Patrício Soares
Perceptual maps
Cognition
Neurocognitive assessment
Clinical variables
Lifestyle
Ageing
title_short The use of multiple correspondence analysis to explore associations between categories of qualitative variables in healthy ageing
title_full The use of multiple correspondence analysis to explore associations between categories of qualitative variables in healthy ageing
title_fullStr The use of multiple correspondence analysis to explore associations between categories of qualitative variables in healthy ageing
title_full_unstemmed The use of multiple correspondence analysis to explore associations between categories of qualitative variables in healthy ageing
title_sort The use of multiple correspondence analysis to explore associations between categories of qualitative variables in healthy ageing
author Costa, Patrício Soares
author_facet Costa, Patrício Soares
Santos, Nadine Correia
Cunha, Pedro
Cotter, Jorge
Sousa, Nuno
author_role author
author2 Santos, Nadine Correia
Cunha, Pedro
Cotter, Jorge
Sousa, Nuno
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Costa, Patrício Soares
Santos, Nadine Correia
Cunha, Pedro
Cotter, Jorge
Sousa, Nuno
dc.subject.por.fl_str_mv Perceptual maps
Cognition
Neurocognitive assessment
Clinical variables
Lifestyle
Ageing
topic Perceptual maps
Cognition
Neurocognitive assessment
Clinical variables
Lifestyle
Ageing
description In press
publishDate 2013
dc.date.none.fl_str_mv 2013-10-09
2013-10-09T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/1822/25613
url http://hdl.handle.net/1822/25613
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2090-2212
10.1155/2013/302163
http://www.hindawi.com/
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Hindawi Publishing Corporation
publisher.none.fl_str_mv Hindawi Publishing Corporation
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
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reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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