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Aggregate Item Response Analysis

Published online by Cambridge University Press:  01 January 2025

Gordon G. Bechtel  and
Chezy Ofir
Gordon G. Bechtel*
Affiliation:
University of Florida
Chezy Ofir
Affiliation:
The Hebrew University of Jerusalem
*
Requests for reprints should be sent to Gordon G. Bechtel, Marketing Department, University of Florida, Gainesville, FL 32611.
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Abstract

A stochastic postulate is given for the multiple-item, successive-intervals scaling of populations. The logistic equivalent of this postulate provides an aggregate item response model in which a unidimensional submodel may be nested. This reduction provides a subtractive conjoint measurement of several items and stimuli on the same latent scale. Generalized-least-squares methods are used to estimate and test the multiple-item model, and its unidimensional reduction, on aggregate survey responses. The entire procedure is illustrated with an analysis of semantic-differential attitude data. This analysis exhibits an item selection procedure that is applicable to various social constructs.

Keywords

logitsuccessive intervalsitem scalabilitycorrelated multinomialsgeneralized least squares

Information

Type
Original Paper
Information
Psychometrika , Volume 53 , Issue 1 , March 1988 , pp. 93 - 107
Copyright
Copyright © 1988 The Psychometric Society

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Footnotes

The authors dedicate this paper to the memory and contributions of Clyde Coombs.

The programming and data analyses for the present paper were carried out by José Ventura of the Department of Industrial and Systems Engineering, and Jerry Meiten of the Department of Statistics, University of Florida.

The study was also supported by the College of Business Administration, University of Florida, and the Faculty of Social Sciences, Hebrew University of Jerusalem.

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