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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
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    References listed on IDEAS

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    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.
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    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.

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