Detecting Violations of Unidimensionality by Order-Restricted Inference Methods
The assumption of unidimensionality and quantitative measurement represents one of the key concepts underlying most of the commonly applied of item response models. The assumption of unidimensionality is frequently tested although most commonly applied methods have been shown having low power agains...
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2016-03-01
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doaj-2199053ec9704b6e84f0883bd3acde612020-11-25T01:37:46ZengFrontiers Media S.A.Frontiers in Applied Mathematics and Statistics2297-46872016-03-01210.3389/fams.2016.00003178510Detecting Violations of Unidimensionality by Order-Restricted Inference MethodsMoritz eHeene0Andrew eKyngdon1Phillip eSckopke2Ludwig Maximilian University of MunichUniversity of Western AustraliaLudwig Maximilian University of MunichThe assumption of unidimensionality and quantitative measurement represents one of the key concepts underlying most of the commonly applied of item response models. The assumption of unidimensionality is frequently tested although most commonly applied methods have been shown having low power against violations of unidimensionality whereas the assumption of quantitative measurement remains in most of the cases only an (implicit) assumption. On the basis of a simulation study it is shown that order restricted inference methods within a Markov Chain Monte Carlo framework can successfully be used to test both assumptions.http://journal.frontiersin.org/Journal/10.3389/fams.2016.00003/fullRasch modeladditive conjoint measurementmodel fitunidimensionalityNonparametric methodsScaling theory |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Moritz eHeene Andrew eKyngdon Phillip eSckopke |
spellingShingle |
Moritz eHeene Andrew eKyngdon Phillip eSckopke Detecting Violations of Unidimensionality by Order-Restricted Inference Methods Frontiers in Applied Mathematics and Statistics Rasch model additive conjoint measurement model fit unidimensionality Nonparametric methods Scaling theory |
author_facet |
Moritz eHeene Andrew eKyngdon Phillip eSckopke |
author_sort |
Moritz eHeene |
title |
Detecting Violations of Unidimensionality by Order-Restricted Inference Methods |
title_short |
Detecting Violations of Unidimensionality by Order-Restricted Inference Methods |
title_full |
Detecting Violations of Unidimensionality by Order-Restricted Inference Methods |
title_fullStr |
Detecting Violations of Unidimensionality by Order-Restricted Inference Methods |
title_full_unstemmed |
Detecting Violations of Unidimensionality by Order-Restricted Inference Methods |
title_sort |
detecting violations of unidimensionality by order-restricted inference methods |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Applied Mathematics and Statistics |
issn |
2297-4687 |
publishDate |
2016-03-01 |
description |
The assumption of unidimensionality and quantitative measurement represents one of the key concepts underlying most of the commonly applied of item response models. The assumption of unidimensionality is frequently tested although most commonly applied methods have been shown having low power against violations of unidimensionality whereas the assumption of quantitative measurement remains in most of the cases only an (implicit) assumption. On the basis of a simulation study it is shown that order restricted inference methods within a Markov Chain Monte Carlo framework can successfully be used to test both assumptions. |
topic |
Rasch model additive conjoint measurement model fit unidimensionality Nonparametric methods Scaling theory |
url |
http://journal.frontiersin.org/Journal/10.3389/fams.2016.00003/full |
work_keys_str_mv |
AT moritzeheene detectingviolationsofunidimensionalitybyorderrestrictedinferencemethods AT andrewekyngdon detectingviolationsofunidimensionalitybyorderrestrictedinferencemethods AT phillipesckopke detectingviolationsofunidimensionalitybyorderrestrictedinferencemethods |
_version_ |
1725057466666844160 |