Estefania J Guevara¹, Melba L Vertel²* and Daniel E Tamara¹

¹ Department of Mathematics and Statistics, Faculty of Exact and Natural Sciences, National University of Colombia, Manizales, Colombia
²Department of Mathematics, Faculty of Education and Sciences, University of Sucre, Sincelejo, Colombia

*Corresponding Author: Melba L Vertel, Department of Mathematics, Faculty of Education and Sciences, University of Sucre, Sincelejo, Colombia.

Received: July 29, 2022; Published: September 28, 2022

Abstract

The main objective of this work is to methodologically compare simple correspondence analysis (ACS) and canonical correspondence analysis (ACC) applied to frequency tables. A theoretical presentation of the weighted principal component analysis (PCA) is made under the "French school of data". The comparison of the two methods refers to putting them in parallel, since they do not point to exactly the same methodological objectives; properties, common and different elements of the methods are presented and illustrated with the example of Urbina and Londoño (2003). This analysis methodology is presented with an application in public health based on the work of Iriarte., et al. (2012). To execute the statistical techniques, the R software, the ade4 and FactoClass packages are used.

Keywords: Multivariate Data Analysis; Simple Correspondence Analysis; Canonical Analysis of Correspondences; Public Health; Statistical Language R

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Citation

Citation: Melba L Vertel., et al. “Comparison between Simple Correspondence Analysis and Canonical Correspondence Analysis: Application in Public Health".Acta Scientific Computer Sciences 4.10 (2022): 74-81.

Copyright

Copyright: © 2022 Melba L Vertel., et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.