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Identifiability of Nonlinear Logistic Test Models

Published online by Cambridge University Press:  01 January 2025

Timo M. Bechger*
Affiliation:
National Institute for Educational Measurement (Cito)
Norman D. Verhelst
Affiliation:
National Institute for Educational Measurement (Cito)
Huub H. F. M. Verstralen
Affiliation:
National Institute for Educational Measurement (Cito)
*
Requests for reprints should be sent to Timo M. Bechger, National Institute of Educational Measurement (Cito), P.O. Box 1034, 6801 MG Arnhem, THE NETHERLANDS. E-Mail: timo.bechger@cito.nl

Abstract

The linear logistic test model (LLTM) specifies the item parameters as a weighted sum of basic parameters. The LLTM is a special case of a more general nonlinear logistic test model (NLTM) where the weights are partially unknown. This paper is about the identifiability of the NLTM. Sufficient and necessary conditions for global identifiability are presented for a NLTM where the weights are linear functions, while conditions for local identifiability are shown to require a model with less restrictions. It is also discussed how these conditions are checked using an algorithm due to Bekker, Merckens, and Wansbeek (1994). Several illustrations are given.

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Type
Articles
Copyright
Copyright © 2001 The Psychometric Society

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