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Merging Groups to Maximize Object Partition Comparison

Published online by Cambridge University Press:  01 January 2025

T. D. Klastorin
T. D. Klastorin*
Affiliation:
University of Washington
*
Requests for reprints should be sent to T. D. Klastorin, 126 Mackenzie Hall DJ-10, University of Washington, Seattle, WA 98195.
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Abstract

The problem of objectively comparing two independently determined partitions of N objects or variables is discussed. A similarity measure based on the simple matching coefficient is defined and related to previously suggested measures. The problem of merging groups in one partition to maximize this similarity measure is discussed and formulated as a mathematical programming problem; such an approach is useful for determining to what extent the groups in one partition merely represent a finer subdivision of the groups in the other partition. By exploiting the structure of the similarity measure, an efficient algorithm is developed to determine which groups (if any) should be merged to maximize partition similarity.

Information

Type
Original Paper
Information
Psychometrika , Volume 45 , Issue 4 , December 1980, pp. 425 - 433
Copyright
Copyright © 1980 The Psychometric Society

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Footnotes

The author gratefully acknowledges the helpful comments and assistance of Mr. R. Ledingham and Mr. R. Flewelling. This paper was supported in part by H.E.W. Contract # 600-76-0143.

References

Reference Notes

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