Hostname: page-component-cd9895bd7-gbm5v Total loading time: 0 Render date: 2025-01-05T15:03:20.183Z Has data issue: false hasContentIssue false

Some Properties of the Correlation Matrix of Dichotomous Guttman Items

Published online by Cambridge University Press:  01 January 2025

Rebecca Zwick*
Affiliation:
Educational Testing Service
*
Requests for reprints should be sent to Rebecca Zwick, Educational Testing Service, Princeton, NJ 08541.

Abstract

Both the elements and the eigenvalues of the Pearson correlation matrix of dichotomous Guttman-scalable items can be expressed as simple functions of the number of items if the score distribution is uniform and there is an equal number of items at each difficulty level. Even when these special conditions do not hold, the correlations can often be expressed in a simple form by assuming a particular score distribution.

Type
Original Paper
Copyright
Copyright © 1987 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.)

Footnotes

The author thanks Neil Dorans, Bob Mislevy, Ledyard R Tucker, and Howard Wainer for their comments.

References

Burt, C. (1953). Scale analysis and factor analysis. British Journal of Statistical Psychology, 6, 523.CrossRefGoogle Scholar
Guttman, L. (1941). The quantification of a class of attributes: A theory and method of scale construction. In Horst, P., Wallin, P., Guttman, L., Wallin, F. B., Clausen, J. A., Reed, R., Rosenthal, E. (Eds.), The prediction of personal adjustment (pp. 319348). New York: Social Science Research Council.Google Scholar
Guttman, L. (1950). The principal components of scale analysis. In Stouffer, S. A., Guttman, L., Suchman, E. A., Lazarsfeld, P. F., Star, S. A., Clausen, J. A. (Eds.), Measurement and prediction (pp. 312361). Princeton: Princeton University Press.Google Scholar
Guttman, L. (1950). Relation of scalogram analysis to other techniques. In Stouffer, S. A., Guttman, L., Suchman, E. A., Lazarsfeld, P. F., Star, S. A., Clausen, J. A. (Eds.), Measurement and prediction (pp. 172212). Princeton: Princeton University Press.Google Scholar
Lord, F. M., Novick, M. (1968). Statistical theories of mental test scores, Reading, MA: Addison-Wesley.Google 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 categorical multivariate data. Psychometrika, 50, 91119.CrossRefGoogle Scholar
Torgerson, W. S. (1958). Theory and methods of scaling, New York: Wiley.Google Scholar