Loglinear Rasch Models for the Analysis of Stability and Change

Loglinear unidimensional and multidimensional Rasch models are considered for analysis of repeated observations of polytomous indicators with ordered response categories. Reparameterizations and parameter restrictions are provided that facilitate specification of a variety of hypotheses about latent...

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Bibliographic Details
Published inPsychometrika Vol. 61; no. 4; p. 629
Main Author Meiser, Thorsten
Format Journal Article
LanguageEnglish
Published 01.12.1996
Subjects
Change
Classification
Goodness of Fit
Hypothesis Testing
Item Response Theory
Log Linear Models
Longitudinal Studies
Measurement Techniques
Polytomous Variables
Rasch Model
Responses
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ISSN0033-3123
DOI10.1007/BF02294040

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Summary:Loglinear unidimensional and multidimensional Rasch models are considered for analysis of repeated observations of polytomous indicators with ordered response categories. Reparameterizations and parameter restrictions are provided that facilitate specification of a variety of hypotheses about latent processes of change. Use of the models is illustrated. (Author/SLD)
ISSN:0033-3123
DOI:10.1007/BF02294040