IDEAS home Printed from https://ideas.repec.org/a/sae/jedbes/v40y2015i3p274-306.html
   My bibliography  Save this article

Modeling Information Accumulation in Psychological Tests Using Item Response Times

Author

Listed:
  • Jochen Ranger

    (Martin-Luther-University Halle-Wittenberg)

  • Jörg-Tobias Kuhn

    (University of Münster)

Abstract

In this article, a latent trait model is proposed for the response times in psychological tests. The latent trait model is based on the linear transformation model and subsumes popular models from survival analysis, like the proportional hazards model and the proportional odds model. Core of the model is the assumption that an unspecified monotone transformation of the response times can be related to latent characteristics of the test taker. The model can be interpreted in terms of an information accumulation process, according to which test takers acquire information until they are able to respond. The rate of information accumulation can be related to the transformation function of the response times. In order to avoid strong distributional assumptions, the rate of information acquisition is approximated in a piecewise manner by a positive spline. The model can be calibrated with marginal maximum likelihood estimation. This allows a standard test of model fit as will be shown. The proposed approach to model estimation and model evaluation is investigated in a simulation study. Finally, the utility of the model is demonstrated in three real data sets.

Suggested Citation

  • Jochen Ranger & Jörg-Tobias Kuhn, 2015. "Modeling Information Accumulation in Psychological Tests Using Item Response Times," Journal of Educational and Behavioral Statistics, , vol. 40(3), pages 274-306, June.
    • Handle: RePEc:sae:jedbes:v:40:y:2015:i:3:p:274-306
    DOI: 10.3102/1076998615583903
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.3102/1076998615583903
    Download Restriction: no
    File URL: https://libkey.io/10.3102/1076998615583903?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Francis Tuerlinckx & Paul Boeck, 2005. "Two interpretations of the discrimination parameter," Psychometrika, Springer;The Psychometric Society, vol. 70(4), pages 629-650, December.
    2. Jochen Ranger & Jorg-Tobias Kuhn, 2012. "A flexible latent trait model for response times in tests," Psychometrika, Springer;The Psychometric Society, vol. 77(1), pages 31-47, January.
    3. Loeys, Tom & Legrand, Catherine & Schettino, Antonio & Pourtois, Gilles, 2014. "Semi-parametric proportional hazards models with crossed random effects for psychometric response times," LIDAM Reprints ISBA 2014035, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    4. Boracchi, Patrizia & Biganzoli, Elia & Marubini, Ettore, 2003. "Joint modelling of cause-specific hazard functions with cubic splines: an application to a large series of breast cancer patients," Computational Statistics & Data Analysis, Elsevier, vol. 42(1-2), pages 243-262, February.
    5. Steven J. Luck & Edward K. Vogel, 1997. "The capacity of visual working memory for features and conjunctions," Nature, Nature, vol. 390(6657), pages 279-281, November.
    6. Cai, Bo & Lin, Xiaoyan & Wang, Lianming, 2011. "Bayesian proportional hazards model for current status data with monotone splines," Computational Statistics & Data Analysis, Elsevier, vol. 55(9), pages 2644-2651, September.
    7. T. Loeys & Y. Rosseel & K. Baten, 2011. "A Joint Modeling Approach for Reaction Time and Accuracy in Psycholinguistic Experiments," Psychometrika, Springer;The Psychometric Society, vol. 76(3), pages 487-503, July.
    8. José-luis Gaviria, 2005. "Increase in Precision when Estimating Parameters in Computer Assisted Testing Using Response Time," Quality & Quantity: International Journal of Methodology, Springer, vol. 39(1), pages 45-69, February.
    9. Jeffrey Douglas & Michael Kosorok & Betty Chewning, 1999. "A latent variable model for discrete multivariate psychometric waiting times," Psychometrika, Springer;The Psychometric Society, vol. 64(1), pages 69-82, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Alan D. Hutson & Albert Vexler, 2018. "A Cautionary Note on Beta Families of Distributions and the Aliases Within," The American Statistician, Taylor & Francis Journals, vol. 72(2), pages 121-129, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Peter W. Rijn & Usama S. Ali, 2018. "A Generalized Speed–Accuracy Response Model for Dichotomous Items," Psychometrika, Springer;The Psychometric Society, vol. 83(1), pages 109-131, March.
    2. Jochen Ranger & Jorg-Tobias Kuhn, 2012. "A flexible latent trait model for response times in tests," Psychometrika, Springer;The Psychometric Society, vol. 77(1), pages 31-47, January.
    3. Tong-Yu Lu & Wai-Yin Poon & Siu Cheung, 2014. "A Unified Framework for the Comparison of Treatments with Ordinal Responses," Psychometrika, Springer;The Psychometric Society, vol. 79(4), pages 605-620, October.
    4. Igor S. Utochkin & Vladislav A. Khvostov & Yulia M. Stakina, 2017. "Ensemble-Based Segmentation in the Perception of Multiple Feature Conjunctions," HSE Working papers WP BRP 78/PSY/2017, National Research University Higher School of Economics.
    5. 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.
    6. Jastrzębski, Jan & Ciechanowska, Iwona & Chuderski, Adam, 2018. "The strong link between fluid intelligence and working memory cannot be explained away by strategy use," Intelligence, Elsevier, vol. 66(C), pages 44-53.
    7. Aki Kondo & Jun Saiki, 2012. "Feature-Specific Encoding Flexibility in Visual Working Memory," PLOS ONE, Public Library of Science, vol. 7(12), pages 1-8, December.
    8. Paola M. V. Rancoita & Morten Valberg & Romano Demicheli & Elia Biganzoli & Clelia Di Serio, 2017. "Tumor dormancy and frailty models: A novel approach," Biometrics, The International Biometric Society, vol. 73(1), pages 260-270, March.
    9. Hongwei Tan & Sebastiaan van Dijken, 2023. "Dynamic machine vision with retinomorphic photomemristor-reservoir computing," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    10. Robert W. Faff & Sebastian Kernbach, 2021. "A visualisation approach for pitching research," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(4), pages 5177-5197, December.
    11. Yuri A. Markov & Natalia A. Tiurina & Igor S. Utochkin, 2018. "Different features are stored independently in visual working memory but mediated by object-based representations," HSE Working papers WP BRP 101/PSY/2018, National Research University Higher School of Economics.
    12. I. Ardoino & E. M. Biganzoli & C. Bajdik & P. J. Lisboa & P. Boracchi & F. Ambrogi, 2012. "Flexible parametric modelling of the hazard function in breast cancer studies," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(7), pages 1409-1421, December.
    13. Jochen Ranger, 2013. "A Note on the Hierarchical Model for Responses and Response Times in Tests of van der Linden (2007)," Psychometrika, Springer;The Psychometric Society, vol. 78(3), pages 538-544, July.
    14. Tullo, Domenico & Faubert, Jocelyn & Bertone, Armando, 2018. "The characterization of attention resource capacity and its relationship with fluid reasoning intelligence: A multiple object tracking study," Intelligence, Elsevier, vol. 69(C), pages 158-168.
    15. Prabhashi W. Withana Gamage & Christopher S. McMahan & Lianming Wang, 2023. "A flexible parametric approach for analyzing arbitrarily censored data that are potentially subject to left truncation under the proportional hazards model," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 29(1), pages 188-212, January.
    16. Steffi Pohl & Esther Ulitzsch & Matthias Davier, 2019. "Using Response Times to Model Not-Reached Items due to Time Limits," Psychometrika, Springer;The Psychometric Society, vol. 84(3), pages 892-920, September.
    17. Minggen Lu & Christopher S. McMahan, 2018. "A partially linear proportional hazards model for current status data," Biometrics, The International Biometric Society, vol. 74(4), pages 1240-1249, December.
    18. Jifan Zhou & Jun Yin & Tong Chen & Xiaowei Ding & Zaifeng Gao & Mowei Shen, 2011. "Visual Working Memory Capacity Does Not Modulate the Feature-Based Information Filtering in Visual Working Memory," PLOS ONE, Public Library of Science, vol. 6(9), pages 1-10, September.
    19. Udo Boehm & Maarten Marsman & Han L. J. Maas & Gunter Maris, 2021. "An Attention-Based Diffusion Model for Psychometric Analyses," Psychometrika, Springer;The Psychometric Society, vol. 86(4), pages 938-972, December.
    20. Nathaniel J. S. Ashby & Stephan Dickert & Andreas Glockner, 2012. "Focusing on what you own: Biased information uptake due to ownership," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 7(3), pages 254-267, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:jedbes:v:40:y:2015:i:3:p:274-306. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.