Hostname: page-component-7b9c58cd5d-f9bf7 Total loading time: 0 Render date: 2025-03-13T10:53:35.234Z Has data issue: false hasContentIssue false
  • English
  • Français

Michael J. Greenacre. Correspondence Analysis in Practice. London: Academic Press, 1993.

Review products

Michael J. Greenacre. Correspondence Analysis in Practice. London: Academic Press, 1993.

Published online by Cambridge University Press:  01 January 2025

Shizuhiko Nishisato
Shizuhiko Nishisato*
Affiliation:
The Ontario Institute for Studies in Education The University of Toronto
Get access Rights & Permissions [Opens in a new window]

Abstract

An abstract is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content.
Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
Book Review
Information
Psychometrika , Volume 61 , Issue 1 , March 1996 , pp. 187 - 190
Copyright
© 1996 The Psychometric Society

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Bock, R. D. (1956). The selection of judges for preference testing. Psychometrika, 21, 349–366.CrossRefGoogle Scholar
Gifi, A. (1981). Nonlinear multivariate analysis, New York: Wiley.Google Scholar
Greenacre, M. J. (1973). Correspondence analysis in practice, London: Academic Press.Google Scholar
Greenacre, M. J. (1984). Theory and applications of correspondence analysis, London, England: Academic Press.Google Scholar
Johnson, P. O. (1950). The quantification of qualitative data in discriminant analysis. Journal of the American Statistical Association, 45, 65076–65076.CrossRefGoogle Scholar
Lebart, L., Morineau, A., Warick, K. M. (1984). Multivariate descriptive statistical analysis, New York: Wiley.Google Scholar
Millones, O. (1991). Dual scaling in the framework of the association and correlation models under maximum likelihood, Canada: University of Toronto.Google Scholar
Nishisato, S. (1980). Analysis of categorical data: Dual scaling and its applications, Toronto: University of Toronto Press.CrossRefGoogle Scholar
Nishisato, S. (1994). Elements of dual scaling, Hillsdale, NJ: Lawrence Erlbaum.Google Scholar
Nishisato, S., Nishisato, I. (1994). Dual scaling in a nutshell, Toronto, Canada: MicroStats.Google Scholar
Nishisato, S., Sheu, W. J. (1980). Piecewise method of reciprocal averages for dual scaling of multiple-choice data. Psychometrika, 45, 467–478.CrossRefGoogle Scholar
Tenenhaus, M., Young, F. W. (1985). An analysis and synthesis of multiple correspondence analysis, optimal scaling, dual scaling, homogeneity analysis and other methods for quantifying multivariate categorical data. Psychometrika, 50, 91–119.CrossRefGoogle Scholar
Torgerson, W. S. (1958). Theory and methods of scaling, New York: Wiley.Google Scholar
van der Heijden, P. G. M. (1987). Correspondence analysis of longitudinal categorical data, Leiden, The Netherlands: DSWO Press.Google Scholar