Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.13/927422

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Title
Non-symmetrical correspondence analysis with concatenation and linear constraints
Author/Creator
Beh, Eric J.;  D'Ambra, Luigi
Institution
The University of Newcastle. Faculty of Science & Information Technology, School of Mathematical and Physical Sciences
Description
Correspondence analysis is a popular statistical technique used to identify graphically the presence, and structure, of association between two or more cross-classified categorical variables. Such a procedure is very useful when it is known that there is a symmetric (two-way) relationship between the variables. When such a relationship is known not to exist, non-symmetrical correspondence analysis is more appropriate as a method of establishing the source of association. This paper highlights some tools that can be used to explore the behaviour of asymmetric categorical variables. These tools consist of confidence regions, the link between non-symmetrical correspondence analysis and the analysis of variance of categorical variables, and the effect of imposing linear constraints. We also explore the application of non-symmetrical correspondence analysis to three-way contingency tables.
Relation
Australian & New Zealand Journal of Statistics Vol. 52, Issue 1, p. 27-44
Publisher Link
http://dx.doi.org/10.1111/j.1467-842X.2009.00564.x
Date
2010
Publisher
Wiley-Blackwell Publishing
Keyword(s)
confidence circles;  Goodman–Kruskal tau index;  Gray–Williams measure of association;  linear constraints
Resource Type
journal article
Identifier
http://hdl.handle.net/1959.13/927422
Identifier
ISSN:1369-1473
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Subject
"Australian & New Zealand Journal of Statistics"
 
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