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A Speeded Item Response Model: Leave the Harder till Later

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  • Yu-Wei Chang
  • Rung-Ching Tsai
  • Nan-Jung Hsu

Abstract

A speeded item response model is proposed. We consider the situation where examinees may retain the harder items to a later test period in a time limit test. With such a strategy, examinees may not finish answering some of the harder items within the allocated time. In the proposed model, we try to describe such a mechanism by incorporating a speeded-effect term into the two-parameter logistic item response model. A Bayesian estimation procedure of the current model using Markov chain Monte Carlo is presented, and its performance over the two-parameter logistic item response model in a speeded test is demonstrated through simulations. The methodology is applied to physics examination data of the Department Required Test for college entrance in Taiwan for illustration. Copyright The Psychometric Society 2014

Suggested Citation

  • Yu-Wei Chang & Rung-Ching Tsai & Nan-Jung Hsu, 2014. "A Speeded Item Response Model: Leave the Harder till Later," Psychometrika, Springer;The Psychometric Society, vol. 79(2), pages 255-274, April.
    • Handle: RePEc:spr:psycho:v:79:y:2014:i:2:p:255-274
    DOI: 10.1007/s11336-013-9336-2
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    References listed on IDEAS

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    1. Jing Cao & S. Stokes, 2008. "Bayesian IRT Guessing Models for Partial Guessing Behaviors," Psychometrika, Springer;The Psychometric Society, vol. 73(2), pages 209-230, June.
    2. Hariharan Swaminathan & Janice Gifford, 1986. "Bayesian estimation in the three-parameter logistic model," Psychometrika, Springer;The Psychometric Society, vol. 51(4), pages 589-601, December.
    3. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
    4. Yuri Goegebeur & Paul Boeck & James Wollack & Allan Cohen, 2008. "A Speeded Item Response Model with Gradual Process Change," Psychometrika, Springer;The Psychometric Society, vol. 73(1), pages 65-87, March.
    5. C. O'Muircheartaigh & I. Moustaki, 1999. "Symmetric pattern models: a latent variable approach to item non‐response in attitude scales," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 162(2), pages 177-194.
    6. Frederic Lord, 1983. "Maximum likelihood estimation of item response parameters when some responses are omitted," Psychometrika, Springer;The Psychometric Society, vol. 48(3), pages 477-482, September.
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    Cited by:

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    5. Yi-Hsuan Lee & Zhiliang Ying, 2015. "A Mixture Cure-Rate Model for Responses and Response Times in Time-Limit Tests," Psychometrika, Springer;The Psychometric Society, vol. 80(3), pages 748-775, September.

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