Goodness-of-fit methods for nonparametric IRT models

Open Access
Authors
Publication date 2015
Host editors
  • L.A. van der Ark
  • D.M. Bolt
  • W.-C. Wang
  • J.A. Douglas
  • S.-M. Chow
Book title Quantitative Psychology Research
Book subtitle The 79th Annual Meeting of the Psychometric Society, Madison, Wisconsin, 2014
ISBN
  • 9783319199764
ISBN (electronic)
  • 9783319199771
Series Springer Proceedings in Mathematics & Statistics
Event 79th Annual Meeting of the Psychometric Society
Pages (from-to) 109-120
Publisher Cham: Springer
Organisations
  • Faculty of Social and Behavioural Sciences (FMG) - Research Institute of Child Development and Education (RICDE)
Abstract
This chapter has three sections. The first section introduces the unidimensionalmonotone latent variable model for data collected by means of a test or a questionnaire. The second section discusses the use of goodness-of-fit methods for statistical models, in particular, item response models such as theunidimensional monotone latent variable model. The third section discusses the use of the conditional association property for testing the goodness-of-fit of the unidimensional monotone latent variable model. It is established that conditional association is well suited for assessing the local independence assumption and a procedure is proposed for identifying locally independent sets of items. The procedure is used in a real-data analysis.
Document type Conference contribution
Language English
Published at https://doi.org/10.1007/978-3-319-19977-1_9
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