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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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    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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    2. 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.
    3. Merkle, Edgar C. & Steyvers, Mark & Mellers, Barbara & Tetlock, Philip E., 2017. "A neglected dimension of good forecasting judgment: The questions we choose also matter," International Journal of Forecasting, Elsevier, vol. 33(4), pages 817-832.
    4. Chun Wang & Gongjun Xu & Zhuoran Shang, 2018. "A Two-Stage Approach to Differentiating Normal and Aberrant Behavior in Computer Based Testing," Psychometrika, Springer;The Psychometric Society, vol. 83(1), pages 223-254, March.
    5. Chun Wang & Gongjun Xu & Zhuoran Shang & Nathan Kuncel, 2018. "Detecting Aberrant Behavior and Item Preknowledge: A Comparison of Mixture Modeling Method and Residual Method," Journal of Educational and Behavioral Statistics, , vol. 43(4), pages 469-501, August.

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