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Evaluating the Conformity of Sociometric Measurements

Published online by Cambridge University Press:  01 January 2025

Lawrence J. Hubert  and
Frank B. Baker
Lawrence J. Hubert*
Affiliation:
University of California, Santa Barbara
Frank B. Baker
Affiliation:
University of Wisconsin, Madison
*
Requests for reprints should be sent to Lawrence Hubert, Department of Educational Psychology, The University of Wisconsin, 1025 West Johnson Street, Madison, Wisconsin, 53706.
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Abstract

The problem of comparing two sociometric matrices, as originally discussed by Katz and Powell in the early 1950’s, is reconsidered and generalized using a different inference model. In particular, the proposed indices of conformity are justified by a regression argument similar to the one used by Somers in presenting his well-known measures of asymmetric ordinal association. A permutation distribution and an associated significance test are developed for the specific hypothesis of “no conformity” reinterpreted as a random matching of the rows and (simultaneously) the columns of one sociometric matrix to the rows and columns of a second. The approximate significance tests that are presented and illustrated with a simple numerical example are based on the first two moments of the permutation distribution, or alternatively, on a random sample from the complete distribution.

Keywords

sociometric measurementpermutation testsociometrynonparametric test
Type
Original Paper
Information
Psychometrika , Volume 43 , Issue 1 , March 1978 , pp. 31 - 41
Copyright
Copyright © 1978 The Psychometric Society

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Footnotes

Partial support for the research of the first author was provided by the National Science Foundation through SOC 75-07860. Equal authorship is implied, The work was done when the first author was at the University of Wisconsin.

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