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The Problem of Local Optimality with OSMOD

Published online by Cambridge University Press:  01 January 2025

Tatsuo Otsu  and
Takayuki Saito
Tatsuo Otsu*
Affiliation:
Department of Behavioral Science Hokkaido University
Takayuki Saito
Affiliation:
Department of Behavioral Science Hokkaido University
*
Requests for reprints should be sent to Tatsuo Otsu, Department of Behavioral Science, Bungakubu, Hokkaido University, Kita 10 Nishi 7, Kita-ku, Sapporo, 060, JAPAN.
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Abstract

The possibility of obtaining locally optimal solutions with categorical data is pointed out for the original version of OSMOD development by Saito and Otsu. A revision of the initialization strategy in OSMOD is suggested, and its effectiveness in diminishing this possibility is demonstrated.

Keywords

categorical datalocal optimaprincipal component analysisnonlinear optimizationOSMOD
Type
Original Paper
Information
Psychometrika , Volume 55 , Issue 3 , September 1990 , pp. 517 - 518
Copyright
Copyright © 1990 The Psychometric Society

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References

Kuhfeld, W. F., Sarle, W. S., & Young, F. W. (1985). Methods of generating model estimates in the PRINQUAL macro. SAS users group international conference proceedings: SUGI (pp. 962–971). Cary, NC: SAS Institute.Google Scholar
Kuhfeld, W. F., & Young, F. W. (1989). PRINCIPALS versus OSMOD: A comment on Saito and Otsu. Psychometrika, 54, 755–756.CrossRefGoogle Scholar
Saito, T., & Otsu, T. (1983). A method of optimal scaling for multivariate ordinal data. Hokkaido Behavioral Science Report, Series M, 5.Google Scholar
Saito, T., & Otsu, T. (1988). A method of optimal scaling for multivariate ordinal data and its extensions. Psychometrika, 53, 5–25.CrossRefGoogle Scholar
Tenenhaus, M., & Vachette, J. L. (1977). PRINQUAL: Un programme d'Analyse en composantes principales d'un ensemble de variables nominales ou numeriques [PRINQUAL: A program for principal component analysis with nominal or numeric variables], Jouy-en-Josas: CESA.Google Scholar