Skip to main content
SpringerLink
Log in
Book cover

Measurement and Multivariate Analysis pp 87–96Cite as

Analysing Dependence in Large Contingency Tables: NonSymmetric Correspondence Analysis and Regression with Optimal Scaling

  • Conference paper

Summary

In this presentation a brief survey is presented of the relative merits of two alternative approaches to the problem of modelling dependence for categorical variables when they have more than a few categories. The first approach is categorical regression with optimal scaling. The other technique is nonsymmetric(al) correspondence analysis. On a very general level, it will be shown to what an extent the techniques are similar and different.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • D’Ambra, L. and Lauro, N. C. (1989). Non symmetrical analysis of three-way contingency tables. In R. Coppi and S. Bolasco (Eds.), Multiway data analysis (pp. 96 301–315 ). Amsterdam: Elsevier.

    Google Scholar 

  • D’Ambra, L. and Lauro, N. C. (1992). Non symmetrical exploratory data analysis. Statistica Applicata, 4, 511–529.

    Google Scholar 

  • Gabriel, K. R. (1971). The biplot graphic display with application to principal component analysis, Biometrika. 58, 453–467.

    Article  MathSciNet  MATH  Google Scholar 

  • Gifi, A. (1990). Nonlinear multivariate analysis. Chicester, UK: Wiley.

    MATH  Google Scholar 

  • Goodman, L. A., and Kruskal, W. H. (1954). Measures of association for cross classifications, Journal of the American Statistical Association, 49, 732–764.

    MATH  Google Scholar 

  • Gray, L. N. and Williams, J. S. (1975). Goodman and Kruskal’s taub. Multiple and partial analogs. Proceedings of the Social Statistics Section of the American Statistical Association (pp. 444–448 ). Washington, DC: ASA

    Google Scholar 

  • Gray, L. N. and Williams, J. S. (1981). Goodman and Kruskal’s taub. Multiple and partial analogs Sociological Methods and Research, 10, 50–62.

    Google Scholar 

  • Greenacre, M. J. (1984). Theory and applications of correspondence analysis. London: Academic Press.

    MATH  Google Scholar 

  • Kroonenberg, P. M. and Lombardo, R. (1998). Nonsymmetric correspondence analysis: A tool for analysing contingency tables with a dependence structure. Multivariate Behavioral Research, 34, 367–396.

    Article  Google Scholar 

  • Lauro, N. C. and Balbi, S. (1995). The analysis of structured qualitative data. In A. Rizzi (Ed.), Some relations between matrices and structures of multidimensional data analysis (pp. 53–92 ). Pisa, Italy: CNR.

    Google Scholar 

  • Lauro, N. C. and D’Ambra, L. (1984). L’Analyse non symétrique des correspondances [Nonsymmetric correspondence analysis]. In E. Diday et al. (Eds.), Data analysis and Informatics III (pp. 433–446 ). Amsterdam: Elsevier.

    Google Scholar 

  • Light, R. J. and Margolin, B. H. (1971). An analysis of variance for categorical data, Journal of the American Statistical Association, 66, 534–544.

    Article  MathSciNet  MATH  Google Scholar 

  • Margolin, B. H. and Light, R. J. (1974). An analysis of variance for categorical data, II: Small sample comparisons with Chi Square and other competitors, Journal of the American Statistical Association, 69, 755–764.

    Article  MathSciNet  MATH  Google Scholar 

  • Maxwell, A. E. (1961). Analyzing qualitative data. London: Methuen

    Google Scholar 

  • Meulman, J. J., Heiser, W..J., and SPSS Inc (2000) Categories 10.0. Chicago, IL: SPSS Inc.

    Google Scholar 

  • Ritov, Y. and Gilula, Z. (1993). Analysis of contingency tables by correspondence models subject to order constraints. Journal of the American Statistical Association, 88, 1380–1387.

    Article  MathSciNet  MATH  Google Scholar 

  • Siciliano, R. (1992). Reduced-rank models for dependence analysis of contingency tables. Statistica Applicata, 4, 481–501.

    Google Scholar 

  • Tucker, L.R. (1960). Intra-individual and inter-individual multidimensionality. In H. Gulliksen, S. Messick (Eds.), Psychological Scaling: Theory and applications (pp. 155–167). New York: Wiley.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Education, Leiden University, Wassenaarseweg 52, Leiden, The Netherlands

    Pieter M. Kroonenberg

Authors
  1. Pieter M. Kroonenberg
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Measurement and Evaluation Program CTL, OISE/UT, The University of Toronto, 252 Bloor Street West, M5S 1V6, Toronto, Ontario, Canada

    Shizuhiko Nishisato (Professor Emeritus) (Professor Emeritus)

  2. Center for Information on Statistical Sciences, The Institute of Statistical Mathematics, 4-6-7 Minami Azabu, 106-8569, Minato-ku, Tokyo, Japan

    Yasumasa Baba (Professor) & Koji Kanefuji (Associate Professor) (Professor) &  (Associate Professor)

  3. Information Complexity & Model Selection Department of Statistics, 336 SMC, The University of Tennessee, 37996-0532, Knoxville, TN, USA

    Hamparsum Bozdogan (McKenzie Professor in Business) (McKenzie Professor in Business)

Rights and permissions

Reprints and permissions

Copyright information

© 2002 Springer Japan

About this paper

Cite this paper

Kroonenberg, P.M. (2002). Analysing Dependence in Large Contingency Tables: NonSymmetric Correspondence Analysis and Regression with Optimal Scaling. In: Nishisato, S., Baba, Y., Bozdogan, H., Kanefuji, K. (eds) Measurement and Multivariate Analysis. Springer, Tokyo. https://doi.org/10.1007/978-4-431-65955-6_9

Download citation

  • DOI: https://doi.org/10.1007/978-4-431-65955-6_9

  • Publisher Name: Springer, Tokyo

  • Print ISBN: 978-4-431-65957-0

  • Online ISBN: 978-4-431-65955-6

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation