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Curvilinear dependency of response accuracy on response time in cognitive tests

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  • Chen, Haiqin
  • De Boeck, Paul
  • Grady, Matthew
  • Yang, Chien-Lin
  • Waldschmidt, David

Abstract

The relationship between response time and accuracy in cognitive tasks is an important topic in experimental cognitive psychology as well as in the domain of cognitive testing, but the relationship is much more difficult to capture for the latter. Using data involving five cognitive tests: three academic achievement tests (knowledge tests) and two reasoning tests (perceptual and quantitative reasoning), the relationship between response time and response accuracy is explored after controlling for possible confounds associated with individual and item differences. The tests are different in terms of contents and type of test (achievement or ability test), but it was nonetheless found for all tests that response accuracy shows the same kind of curvilinear dependency on response time. Accuracy rates first increase rather rapidly and then decrease more slowly as a function of response time. The turning point came earlier for the three knowledge tests than for the two ability tests. The results are not easily reconcilable with simple principles that may apply to tasks used in cognitive experimental psychology. Possible explanations refer to discontinuities in the cognitive processes such as switching strategies, or a decline of cognitive efficiency and increasing cognitive depletion with passing time while working on problems that take much more time than the common tasks in experimental psychology.

Suggested Citation

  • Chen, Haiqin & De Boeck, Paul & Grady, Matthew & Yang, Chien-Lin & Waldschmidt, David, 2018. "Curvilinear dependency of response accuracy on response time in cognitive tests," Intelligence, Elsevier, vol. 69(C), pages 16-23.
    • Handle: RePEc:eee:intell:v:69:y:2018:i:c:p:16-23
    DOI: 10.1016/j.intell.2018.04.001
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    References listed on IDEAS

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    1. Wim van der Linden, 2007. "A Hierarchical Framework for Modeling Speed and Accuracy on Test Items," Psychometrika, Springer;The Psychometric Society, vol. 72(3), pages 287-308, September.
    2. Chun Wang & Zhewen Fan & Hua-Hua Chang & Jeffrey A. Douglas, 2013. "A Semiparametric Model for Jointly Analyzing Response Times and Accuracy in Computerized Testing," Journal of Educational and Behavioral Statistics, , vol. 38(4), pages 381-417, August.
    3. Maria Bolsinova & Jesper Tijmstra, 2016. "Posterior Predictive Checks for Conditional Independence Between Response Time and Accuracy," Journal of Educational and Behavioral Statistics, , vol. 41(2), pages 123-145, April.
    4. Wim Linden & Cees Glas, 2010. "Statistical Tests of Conditional Independence Between Responses and/or Response Times on Test Items," Psychometrika, Springer;The Psychometric Society, vol. 75(1), pages 120-139, March.
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    Cited by:

    1. Inhan Kang & Minjeong Jeon & Ivailo Partchev, 2023. "A Latent Space Diffusion Item Response Theory Model to Explore Conditional Dependence between Responses and Response Times," Psychometrika, Springer;The Psychometric Society, vol. 88(3), pages 830-864, September.
    2. Inhan Kang & Paul Boeck & Roger Ratcliff, 2022. "Modeling Conditional Dependence of Response Accuracy and Response Time with the Diffusion Item Response Theory Model," Psychometrika, Springer;The Psychometric Society, vol. 87(2), pages 725-748, June.
    3. Sun-Joo Cho & Sarah Brown-Schmidt & Paul De Boeck & Matthew Naveiras & Si On Yoon & Aaron Benjamin, 2023. "Incorporating Functional Response Time Effects into a Signal Detection Theory Model," Psychometrika, Springer;The Psychometric Society, vol. 88(3), pages 1056-1086, September.
    4. Kang, Inhan & De Boeck, Paul & Partchev, Ivailo, 2022. "A randomness perspective on intelligence processes," Intelligence, Elsevier, vol. 91(C).
    5. Th'eo Durandard & Matteo Camboni, 2024. "Under Pressure: Comparative Statics for Optimal Stopping Problems in Nonstationary Environments," Papers 2402.06999, arXiv.org.

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