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A Minimum-Cost Network-Flow Solution to the Case V Thurstone Scaling Problem

Published online by Cambridge University Press:  01 January 2025

James M. Lattin
James M. Lattin*
Affiliation:
Graduate School of Business, Stanford University
*
Requests for reprints should he sent to James M. Lattin, Graduate School of Business, Stanford University, Stanford, California, 94305.
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Abstract

This paper presents an approach for determining unidimensional scale estimates that are relatively insensitive to limited inconsistencies in paired comparisons data. The solution procedure, shown to be a minimum-cost network-flow problem, is presented in conjunction with a sensitivity diagnostic that assesses the influence of a single pairwise comparison on traditional Thurstone (ordinary least squares) scale estimates. When the diagnostic indicates some source of distortion in the data, the network technique appears to be more successful than Thurstone scaling in preserving the interval scale properties of the estimates.

Keywords

Thurstone scalingoutlierssensitivity diagnosticnetwork optimization
Type
Original Paper
Information
Psychometrika , Volume 55 , Issue 2 , June 1990 , pp. 353 - 370
Copyright
Copyright © 1990 The Psychometric Society

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Footnotes

My special thanks go to Alvin Silk, Thomas Magnanti, and Roy Welsch for their support and advice throughout the formative stages of this paper, and to V. Srinivasan for his helpful comments on a later draft of this paper. I also wish to thank the Editor, Associate Editor, and two reviewers for their constructive suggestions.

James M. Lattin is Associate Professor of Marketing and Management Science and the James and Doris McNamara Faculty Fellow for 1988-1989.

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