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Some Remarks on Scheiblechner's Treatment of ISOP Models

Published online by Cambridge University Press:  01 January 2025

Brian W. Junker
Brian W. Junker*
Affiliation:
Department of Statistics, Carnegie Mellon University
*
Requests for reprints should be sent to Brian W. Junker, Department of Statistics, Carnegie Mellon University, Pittsburgh, PA 15213-3890.
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Abstract

Scheiblechner (1995) proposes a probabilistic axiomatization of measurement called ISOP (isotonic ordinal probabilistic models) that replaces Rasch's (1980) specific objectivity assumptions with two interesting ordinal assumptions. Special cases of Scheiblechner's model include standard unidimensional factor analysis models in which the loadings are held constant, and the Rasch model for binary item responses. Closely related are the doubly-monotone item response models of Mokken (1971; see also Mokken & Lewis, 1982; Sijtsma, 1988; Molenaar, 1991; Sijtsma & Junker, 1996; and Sijtsma & Hemker, in press). More generally, strictly unidimensional latent variable models have been considered in some detail by Holland and Rosenbaum (1986), Ellis and van den Wollenberg (1993), and Junker (1990, 1993). The purpose of this note is to provide connections with current research in foundations and nonparametric latent variable and item response modeling that are missing from Scheiblechner's (1995) paper, and to point out important related work by Hemker, Sijtsma, Molenaar, & Junker (1996, 1997), Ellis and Junker (in press) and Junker and Ellis (1997). We also discuss counterexamples to three major theorems in the paper. By carrying out these three tasks, we hope to provide researchers interested in the foundations of measurement and item response modeling the opportunity to give the ISOP approach the careful attention it deserves.

Keywords

item response theory foundationsisotonic ordinal probabilistic modelsstrict unidimensionalitycomonotonicitymanifest monotonicitycovariances given a sumstochastic ordering
Type
Notes And Comments
Information
Psychometrika , Volume 63 , Issue 1 , March 1998 , pp. 73 - 85
Copyright
Copyright © 1998 The Psychometric Society

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Footnotes

This research was supported by the National Science Foundation, Grant DMS-94.04438. I thank the Editor and three anonymous referees for careful readings that improved the completeness of this note.

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