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Polytomous Latent Scales for the Investigation of the Ordering ofItems

Polytomous Latent Scales for the Investigation of the Ordering ofItems We propose three latent scales within the framework of nonparametric item response theory for polytomously scored items. Latent scales are models that imply an invariant item ordering, meaning that the order of the items is the same for each measurement value on the latent scale. This ordering property may be important in, for example, intelligence testing and person-fit analysis. We derive observable properties of the three latent scales that can each be used to investigate in real data whether the particular model adequately describes the data. We also propose a methodology for analyzing test data in an effort to find support for a latent scale, and we use two real-data examples to illustrate the practical use of this methodology. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Psychometrika Cambridge University Press

Polytomous Latent Scales for the Investigation of the Ordering ofItems

Psychometrika , Volume 76 (2) – Jan 27, 2011

 
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References (53)

Publisher
Cambridge University Press
Copyright
Copyright © 2011 by The Psychometric Society
Subject
Psychology; Statistical Theory and Methods; Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law; Psychometrics; Assessment, Testing and Evaluation
ISSN
0033-3123
eISSN
1860-0980
DOI
10.1007/s11336-010-9199-8
Publisher site
See Article on Publisher Site

Abstract

We propose three latent scales within the framework of nonparametric item response theory for polytomously scored items. Latent scales are models that imply an invariant item ordering, meaning that the order of the items is the same for each measurement value on the latent scale. This ordering property may be important in, for example, intelligence testing and person-fit analysis. We derive observable properties of the three latent scales that can each be used to investigate in real data whether the particular model adequately describes the data. We also propose a methodology for analyzing test data in an effort to find support for a latent scale, and we use two real-data examples to illustrate the practical use of this methodology.

Journal

PsychometrikaCambridge University Press

Published: Jan 27, 2011

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