Hostname: page-component-745bb68f8f-cphqk Total loading time: 0 Render date: 2025-01-07T19:28:44.193Z Has data issue: false hasContentIssue false
  • English
  • Français

On the Johnson-Neyman Technique and Some Extensions Thereof

Published online by Cambridge University Press:  01 January 2025

Richard F. Potthoff
Richard F. Potthoff*
Affiliation:
University of North Carolina
Get access Rights & Permissions [Opens in a new window]

Abstract

The Johnson-Neyman technique is a statistical tool used most frequently in educational and psychological applications. This paper starts by briefly reviewing the Johnson-Neyman technique and suggesting when it should and should not be used; then several different modifications and extensions of the Johnson-Neyman technique, all of them conceptually simple, are proposed. The close relation between confidence intervals and regions of significance of the Johnson-Neyman type is pointed out. The problem of what to do when more than two groups are being compared is considered. The situation of more than one criterion variable is also considered.

Type
Original Paper
Information
Psychometrika , Volume 29 , Issue 3 , September 1964 , pp. 241 - 256
Copyright
Copyright © 1964 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

*

This research was supported in part by Educational Testing Service, and in part by the Mathematics Division of the Air Force Office of Scientific Research.

References

Abelson, R. P. A note on the Neyman-Johnson technique. Psychometrika, 1953, 18, 213–218.CrossRefGoogle Scholar
Dunn, O. J. Multiple comparisons among means. J. Amer. statist. Ass., 1961, 56, 52–64.CrossRefGoogle Scholar
Fisher, R. A. Statistical methods for research workers (10th ed.), Edinburgh: Oliver and Boyd, 1946.Google Scholar
Johnson, P. O. and Fay, L. C. The Johnson-Neyman technique, its theory and application. Psychometrika, 1950, 15, 349–367.CrossRefGoogle Scholar
Johnson, P. O. and Neyman, J. Tests of certain linear hypotheses and their application to some educational problems. Statist. res. Mem., 1936, 1, 57–93.Google Scholar
Roy, S. N. Some aspects of multivariate analysis, New York: Wiley, 1957.Google Scholar
Roy, S. N. and Bose, R. C. Simultaneous confidence interval estimation. Ann. math. Statist., 1953, 24, 513–536.CrossRefGoogle Scholar
Scheffé, H. The analysis of variance, New York: Wiley, 1959.Google Scholar