The Use of Multiple Correspondence Analysis to Explore Associations between Categories of Qualitative Variables in Healthy Ageing
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, and...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2013-01-01
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| Series: | Journal of Aging Research |
| Online Access: | http://dx.doi.org/10.1155/2013/302163 |
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| _version_ | 1832559926742876160 |
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| author | Patrício Soares Costa Nadine Correia Santos Pedro Cunha Jorge Cotter Nuno Sousa |
| author_facet | Patrício Soares Costa Nadine Correia Santos Pedro Cunha Jorge Cotter Nuno Sousa |
| author_sort | Patrício Soares Costa |
| collection | DOAJ |
| description | 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, and MCA was used to detect and explore relationships between cognitive, clinical, physical, and lifestyle variables. Two PCA dimensions were identified (general cognition/executive function and memory), and two MCA dimensions were retained. Poorer cognitive performance was associated with older age, less school years, unhealthier lifestyle indicators, and presence of pathology. The first MCA dimension indicated the clustering of general/executive function and lifestyle indicators and education, while the second association was between memory and clinical parameters and age. The clustering analysis with object scores method was used to identify groups sharing similar characteristics. 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 if a relationship exists and how variables are related, and offering statistical results that can be seen both analytically and visually. |
| format | Article |
| id | doaj-art-b75319e0341d418a8a8e225b3a0ee6a5 |
| institution | Kabale University |
| issn | 2090-2204 2090-2212 |
| language | English |
| publishDate | 2013-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Aging Research |
| spelling | doaj-art-b75319e0341d418a8a8e225b3a0ee6a52025-02-03T01:29:00ZengWileyJournal of Aging Research2090-22042090-22122013-01-01201310.1155/2013/302163302163The Use of Multiple Correspondence Analysis to Explore Associations between Categories of Qualitative Variables in Healthy AgeingPatrício Soares Costa0Nadine Correia Santos1Pedro Cunha2Jorge Cotter3Nuno Sousa4Life and Health Sciences Research Institute (ICVS), School of Health Sciences, University of Minho, 4710-057 Braga, PortugalLife and Health Sciences Research Institute (ICVS), School of Health Sciences, University of Minho, 4710-057 Braga, PortugalLife and Health Sciences Research Institute (ICVS), School of Health Sciences, University of Minho, 4710-057 Braga, PortugalLife and Health Sciences Research Institute (ICVS), School of Health Sciences, University of Minho, 4710-057 Braga, PortugalLife and Health Sciences Research Institute (ICVS), School of Health Sciences, University of Minho, 4710-057 Braga, PortugalThe 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, and MCA was used to detect and explore relationships between cognitive, clinical, physical, and lifestyle variables. Two PCA dimensions were identified (general cognition/executive function and memory), and two MCA dimensions were retained. Poorer cognitive performance was associated with older age, less school years, unhealthier lifestyle indicators, and presence of pathology. The first MCA dimension indicated the clustering of general/executive function and lifestyle indicators and education, while the second association was between memory and clinical parameters and age. The clustering analysis with object scores method was used to identify groups sharing similar characteristics. 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 if a relationship exists and how variables are related, and offering statistical results that can be seen both analytically and visually.http://dx.doi.org/10.1155/2013/302163 |
| spellingShingle | Patrício Soares Costa Nadine Correia Santos Pedro Cunha Jorge Cotter Nuno Sousa The Use of Multiple Correspondence Analysis to Explore Associations between Categories of Qualitative Variables in Healthy Ageing Journal of Aging Research |
| title | 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_short | The Use of Multiple Correspondence Analysis to Explore Associations between Categories of Qualitative Variables in Healthy Ageing |
| title_sort | use of multiple correspondence analysis to explore associations between categories of qualitative variables in healthy ageing |
| url | http://dx.doi.org/10.1155/2013/302163 |
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