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Statistical Applications of Linear Assignment

Published online by Cambridge University Press:  01 January 2025

Lawrence J. Hubert
Lawrence J. Hubert*
Affiliation:
The University of California, Santa Barbara
*
Requests for reprints should be sent to: Lawrence J. Hubert, Graduate School of Education, The University of California, Santa Barbara, California, 93106.
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Abstract

A comprehensive statistical framework is presented which encompasses a wide range of existing nonparametric methods. The basic strategy, referred to as linear assignment (LA), depends on a simple index of correspondence defined between two object sets that have been matched in some a priori manner. In this broad sense, LA can be interpreted as a general correlational technique. A variety of extensions are discussed along with the attendant problems of significance testing and the construction of normalized descriptive indices.

Keywords

linear assignmentpermutation testsnonparametric statisticscorrelationspatial statisticsconcordance

Information

Type
Original Paper
Information
Psychometrika , Volume 49 , Issue 4 , December 1984 , pp. 449 - 473
Copyright
Copyright © 1984 The Psychometric Society

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Footnotes

Given as the Presidential Address to the Psychometric Society's Annual Meeting, June, 1984. I wish to thank M. Jambu, C. Perruchet, and their colleagues at the Centre National d'Études des Télécommunications for assistance during the summer of 1983 when most of this paper was written. Partial support for this research was also supplied by the National Institute of Justice, Grant #82-IJ-CX-0019.

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