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Some Interpretative Tools for Non-Symmetrical Correspondence Analysis

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Abstract

Non-symmetrical correspondence analysis (NSCA) is a very practical statistical technique for the identification of the structure of association between asymmetrically related categorical variables forming a contingency table. This paper considers some tools that can be used to numerically and graphically explore in detail the association between these variables and include the use of confidence regions, the establishment of the link between NSCA and the analysis of variance of categorical variables, and the effect of imposing linear constraints on a variable.

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Authors and Affiliations

  1. School of Computing and Mathematics, University of Western Sydney, Locked Bag 1797, Penrith South DC, NSW, 1797, Australia

    Eric J. Beh

  2. Universita di Napoli “Federico II”, via Cynthia Monte Sant’Angelo, 80126, Napoli, Italy

    Luigi D’Ambra

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  1. Eric J. Beh
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  2. Luigi D’Ambra
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Correspondence to Eric J. Beh.

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The authors would like to thank the anonymous referees for their comments and suggestions during the preparation of this paper.

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Beh, E.J., D’Ambra, L. Some Interpretative Tools for Non-Symmetrical Correspondence Analysis. J Classif 26, 55–76 (2009). https://doi.org/10.1007/s00357-009-9025-0

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