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Loglinear Rasch models for the Analysis of Stability and Change

Published online by Cambridge University Press:  01 January 2025

Thorsten Meiser
Thorsten Meiser*
Affiliation:
University of Bonn
*
Requests for reprints should be sent to Thorsten Meiser, Psychologisches Institut der Universitfit Bonn, Römerstr. 164, D-53117 Bonn, GERMANY.
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Abstract

Loglinear unidimensional and multidimensional Rasch models are considered for the analysis of repeated observations of polytomous indicators with ordered response categories. Reparameterizations and parameter restrictions are provided which facilitate specification of a variety of hypotheses about latent processes of change. Models of purely quantitative change in latent traits are proposed as well as models including structural change. A conditional likelihood ratio test is presented for the comparison of unidimensional and multiple scales Rasch models. In the context of longitudinal research, this renders possible the statistical test of homogeneity of change against subject-specific change in latent traits. Applications to two empirical data sets illustrate the use of the models.

Keywords

Rasch modelmultidimensional Rasch modelnonstandard loglinear modelmeasurement of changegoodness of fit testing
Type
Original Paper
Information
Psychometrika , Volume 61 , Issue 4 , December 1996 , pp. 629 - 645
Copyright
Copyright © 1996 The Psychometric Society

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Footnotes

The author is greatly indebted to Ulf Böckenholt, Rolf Langeheine, and several anonymous reviewers for many helpful suggestions.

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