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Increasing unidimensional measurement precision using a multidimensional item response model approach

Author(s): Steffen Brandt | Brent Duckor

Journal: Psychological Test and Assessment Modeling
ISSN 2190-0493

Volume: 55;
Issue: 2;
Start page: 148;
Date: 2013;
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Keywords: item response theory | local item dependence | generalized subdimension model | multidimensionality | hierarchical models | instrument Validation

In recent years the estimation of unidimensional abilities for instruments with subtests has been a focus of item response theory. Different hierarchical models, which assume a common unidimensional latent trait and several subtest specific latent traits, have been proposed in order to cope with local item dependencies due to subtests. In contrast to these models, the generalized subdimension model (GSM) allows for the estimation of a latent mean ability based on multidimensional latent traits. Examining a small data set (n=72) this article examines the implicit weighting of the unidimensional model in contrast to the explicit weighting of the GSM to improve measurement precision.
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