Simple and multiple correspondence analysis for ordinal-scale variables using orthogonal polynomials

Title: Simple and multiple correspondence analysis for ordinal-scale variables using orthogonal polynomials
Creator: Lombardo, Rosario; Beh, Eric J.
Relation: Journal of Applied Statistics Vol. 37, Issue 12, p. 2101-2116
Publisher Link: http://dx.doi.org/10.1080/02664760903247692
Publisher: Routledge
Resource Type: journal article
Date: 2010
Description: Correspondence analysis (CA) has gained a reputation for being a very useful statistical technique for determining the nature of association between two or more categorical variables. For simple and multiple CA, the singular value decomposition (SVD) is the primary tool used and allows the user to construct a low-dimensional space to visualize this association. As an alternative to SVD, one may consider the bivariate moment decomposition (BMD), a method of decomposition that involves using orthogonal polynomials to reflect the structure of ordered categorical responses. When the features of BMD are combined with SVD, a hybrid decomposition (HD) is formed. The aim of this paper is to show the applicability of HD when performing simple and multiple CA.
Subject: multiple correspondence analysis; ordinal-scale variables; singular value decomposition; bivariate moment decomposition; orthogonal polynomials; hybrid decomposition
Identifier: http://hdl.handle.net/1959.13/929939
Identifier: uon:10713
Identifier: ISSN:0266-4763
Language: eng
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