From correspondence analysis to multiple and joint correspondence analysis

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• dc.contributor.author Greenacre, Michaelca
• dc.contributor.other Universitat Pompeu Fabra. Departament d'Economia i Empresa
• dc.date.accessioned 2017-07-26T10:50:52Z
• dc.date.available 2017-07-26T10:50:52Z
• dc.date.issued 2005-09-01
• dc.date.modified 2017-07-23T02:09:47Z
• dc.description.abstract The generalization of simple (two-variable) correspondence analysis to more than two categorical variables, commonly referred to as multiple correspondence analysis, is neither obvious nor well-defined. We present two alternative ways of generalizing correspondence analysis, one based on the quantification of the variables and intercorrelation relationships, and the other based on the geometric ideas of simple correspondence analysis. We propose a version of multiple correspondence analysis, with adjusted principal inertias, as the method of choice for the geometric definition, since it contains simple correspondence analysis as an exact special case, which is not the situation of the standard generalizations. We also clarify the issue of supplementary point representation and the properties of joint correspondence analysis, a method that visualizes all two-way relationships between the variables. The methodology is illustrated using data on attitudes to science from the International Social Survey Program on Environment in 1993.
• dc.format.mimetype application/pdfca
• dc.identifier https://econ-papers.upf.edu/ca/paper.php?id=883
• dc.identifier.citation chapter 2 of Multiple Correspondence Analysis and Related Methods, Chapman & Hall/CRC, 2006
• dc.identifier.uri http://hdl.handle.net/10230/932
• dc.language.iso eng
• dc.relation.ispartofseries Economics and Business Working Papers Series; 883
• dc.rights L'accés als continguts d'aquest document queda condicionat a l'acceptació de les condicions d'ús establertes per la següent llicència Creative Commons
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/
• dc.subject.keyword correspondence analysis
• dc.subject.keyword eigendecomposition
• dc.subject.keyword joint correspondence analysis
• dc.subject.keyword multivariate categorical data
• dc.subject.keyword questionnaire data
• dc.subject.keyword singular value decomposition
• dc.subject.keyword Statistics, Econometrics and Quantitative Methods
• dc.title From correspondence analysis to multiple and joint correspondence analysisca
• dc.type info:eu-repo/semantics/workingPaper