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A Note on the Off-Block-Diagonal Approximation of the Burt Matrix as Applied in Joint Correspondence Analysis

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Classification, Data Analysis, and Data Highways

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Abstract

Joint correspondence analysis (JCA) is a commonly applied variation of multiple correspondence analysis (MCA) where the block-diagonal part of the Burt matrix is not considered in the fit. Examples shown here underline that this approach may in some cases lead to ambiguous results which may violate desirable properties of the representation.

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References

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Author information

Authors and Affiliations

  1. Institut für Medizinische Informatik, Biometrie und Epidemiologie, ME der Universität GHS Essen, Germany

    Johannes Faßbinder

Authors
  1. Johannes Faßbinder
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Editor information

Editors and Affiliations

  1. University of Potsdam, August-Bebel-Str. 89, D-14482, Potsdam, Germany

    Ingo Balderjahn

  2. RWTH Aachen, Templergraben 55, D-52062, Aachen, Germany

    Rudolf Mathar

  3. University of Mannheim, Schloß, D-68131, Mannheim, Germany

    Martin Schader

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© 1998 Springer-Verlag Berlin · Heidelberg

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Faßbinder, J. (1998). A Note on the Off-Block-Diagonal Approximation of the Burt Matrix as Applied in Joint Correspondence Analysis. In: Balderjahn, I., Mathar, R., Schader, M. (eds) Classification, Data Analysis, and Data Highways. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-72087-1_15

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  • DOI: https://doi.org/10.1007/978-3-642-72087-1_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63909-1

  • Online ISBN: 978-3-642-72087-1

  • eBook Packages: Springer Book Archive

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