Hostname: page-component-74656f9884-j7cmm Total loading time: 0 Render date: 2026-11-10T11:31:24.982Z Has data issue: false hasContentIssue false
  • English
  • Français

An Interactive Preference Ordering Model and its Monte Carlo Evaluation

Published online by Cambridge University Press:  01 January 2025

Thomas J. Reynolds  and
Norman Cliff
Thomas J. Reynolds*
Affiliation:
The University of Texas, Dallas
Norman Cliff
Affiliation:
University of Southern California
*
Requests for reprints should be sent to Thomas J. Reynolds, Graduate School of Management, Richardson, TX 75080.
Get access Rights & Permissions [Opens in a new window]

Abstract

A computer-interactive preference ordering procedure that is based on assumed transitivity of relations is described. The procedure includes features that are designed to make it robust in the presence of inconsistency. With errorless data, the method will find the underlying order in close to log2n! comparisons. Two simulation studies are described where the responses are assumed to follow the Thurstone Case V model. It was found that the method produces orders that are more valid than does a considerably larger preselected subset of pairs.

Keywords

Simulation StudyPublic PolicyStatistical TheoryVersus ModelCase Versus

Information

Type
Original Paper
Information
Psychometrika , Volume 49 , Issue 2 , June 1984 , pp. 247 - 255
Copyright
Copyright © 1984 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.)

Article purchase

Temporarily unavailable

Footnotes

This research was supported in part by Public Health Service Grant MH 16474. It was part of a larger project, and major contributions were made by Jerald F. Kehoe and Rex S. Green.

References

Cliff, N. (1975). Complete orders from incomplete data: Interactive ordering and tailored testing. Psychological Bulletin, 82, 289–302.CrossRefGoogle Scholar
Cliff, N., Cudeck, R. & McCormick, D. J. (1979). Evaluation of implied orders tailored testing with simulation data. Applied Psychological Measurement, 3, 495–514.CrossRefGoogle Scholar
Coombs, C. H. (1964). A theory of data, New York: Wiley.Google Scholar
Green, R. S. (1974). A Monte Carlo evaluation of a computer-interactive extended transitivity dominance scaling model. Unpublished doctoral dissertation, University of Southern California.Google Scholar
Harary, F., Norman, R., & Cartwright, D. (1965). Structural Models: An introduction to the theory of directed graphs, New York: Wiley.Google Scholar
Kehoe, J., & Cliff, N. (1975). INTERORD: A computer-interactive FORTRAN IV program for developing simple orders. Educational and Psychological Measurement, 35, 675–678.CrossRefGoogle Scholar
Knuth, D. E. (1973). The art of computer programming. V. 3. Sorting and searching, Reading, Mass.: Addison-Wesley.Google Scholar
O'Neil, P. E., & O'Neil, E. J. (1973). A fast expected time algorithm for Boolean matrix multiplication and transitive closure. Information and Control, 22, 132–138.CrossRefGoogle Scholar
Reynolds, T. J. (1975). An interactive preference ordering model in APL and its Monte Carlo evaluation. Unpublished Master's Thesis, University of Southern California.Google Scholar
Reynolds, T. J. & Cliff, N. (1975). A computer-interactive APL program for recovering simple orders. Educational and Psychological Measurement, 35, 671–675.CrossRefGoogle Scholar
Spence, I. & Domoney, D. W. (1974). Single subject incomplete designs for nonmetric multidimensional scaling. Psychometrika, Vol. 39, No. 4.CrossRefGoogle Scholar
Thurstone, L. L. (1927). A law of comparative judgment. Psychological Review, 34, 273–286.CrossRefGoogle Scholar