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Item Response Model from a Distance Perspective

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  • Budiaji, Weksi

Abstract

There are two frameworks of models in item response theory (IRT), unipolar and bipolar models. The bipolar models usually use a distance approach, but this approach has not yet been applied in the unipolar models. Five examples of unipolar models are the Rasch, the two parameter logistic (2PL) model, the rating scale model (RSM), the multidimensional Rasch model (MRM), and the multidimensional 2PL model (M2PLM). We will show that unipolar models can also be built using distances. Therefore, the Ideal Point Classfication (IPC) model is used. The parameters of the IPC model are linearly related to those of the unipolar models. The item midpoint positions and the person positions in the IPC model are the shrinkage version of the location parameters and the ability parameters, respectively.

Suggested Citation

  • Budiaji, Weksi, 2012. "Item Response Model from a Distance Perspective," Thesis Commons wcbu9, Center for Open Science.
  • Handle: RePEc:osf:thesis:wcbu9
    DOI: 10.31219/osf.io/wcbu9
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    References listed on IDEAS

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    1. Yoshio Takane, 1987. "Analysis of contingency tables by ideal point discriminant analysis," Psychometrika, Springer;The Psychometric Society, vol. 52(4), pages 493-513, December.
    2. Mark Rooij, 2009. "Ideal Point Discriminant Analysis Revisited with a Special Emphasis on Visualization," Psychometrika, Springer;The Psychometric Society, vol. 74(2), pages 317-330, June.
    3. Yoshio Takane & Hamparsum Bozdogan & Tadashi Shibayama, 1987. "Ideal point discriminant analysis," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 371-392, September.
    4. David Andrich, 1978. "A rating formulation for ordered response categories," Psychometrika, Springer;The Psychometric Society, vol. 43(4), pages 561-573, December.
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