Hostname: page-component-745bb68f8f-grxwn Total loading time: 0 Render date: 2025-01-08T11:13:36.979Z Has data issue: false hasContentIssue false
  • English
  • Français

Approximating Maximum Test Validity by a Non-Parametric Method

Published online by Cambridge University Press:  01 January 2025

Harold Webster
Harold Webster*
Affiliation:
University of Kentucky
Get access Rights & Permissions [Opens in a new window]

Abstract

The Gleser-DuBois conditions for selecting from a number of test items those which will maximize the correlation between total test score and criterion will degenerate into expressions requiring only item counts on total distributions and the upper halves of distributions. A grouping convention for scores near medians is recommended. The inefficiency of the method is easily compensated for, because, regardless of the size of the sample, only standard test-scoring equipment and brief computations are required. A procedure is outlined, and some applications are discussed.

Type
Original Paper
Information
Psychometrika , Volume 18 , Issue 3 , September 1953 , pp. 207 - 211
Copyright
Copyright © 1953 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

*

Now at Vassar College, Poughkeepsie, New York.

†

Gleser, G. C, and DuBois, P. H. A successive approximation method of maximizing test validity. Psychometrika, 1951, 16, 129–139.

‡

Guilford, J. P. Fundamental statistics in psychology and education (2nd Ed.). New York: McGraw-Hill, 1950.

§

The convention used here and in subsequent expressions is that “positive” is read after >, “negative” after <.