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A Multivariate Multilevel Approach to the Modeling of Accuracy and Speed of Test Takers

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  • R. Klein Entink
  • J.-P. Fox
  • W. Linden

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  • R. Klein Entink & J.-P. Fox & W. Linden, 2009. "A Multivariate Multilevel Approach to the Modeling of Accuracy and Speed of Test Takers," Psychometrika, Springer;The Psychometric Society, vol. 74(1), pages 21-48, March.
    • Handle: RePEc:spr:psycho:v:74:y:2009:i:1:p:21-48
    DOI: 10.1007/s11336-008-9075-y
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    References listed on IDEAS

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    1. McCulloch, Robert E. & Polson, Nicholas G. & Rossi, Peter E., 2000. "A Bayesian analysis of the multinomial probit model with fully identified parameters," Journal of Econometrics, Elsevier, vol. 99(1), pages 173-193, November.
    2. Eric Bradlow & Howard Wainer & Xiaohui Wang, 1999. "A Bayesian random effects model for testlets," Psychometrika, Springer;The Psychometric Society, vol. 64(2), pages 153-168, June.
    3. S. Rabe-Hesketh & A. Skrondal, 2001. "Parameterization of Multivariate Random Effects Models for Categorical Data," Biometrics, The International Biometric Society, vol. 57(4), pages 1256-1263, December.
    4. 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.
    5. Sinharay S. & Stern H.S., 2002. "On the Sensitivity of Bayes Factors to the Prior Distributions," The American Statistician, American Statistical Association, vol. 56, pages 196-201, August.
    6. Jean-Paul Fox & Cees Glas, 2001. "Bayesian estimation of a multilevel IRT model using gibbs sampling," Psychometrika, Springer;The Psychometric Society, vol. 66(2), pages 271-288, June.
    7. A. Béguin & C. Glas, 2001. "MCMC estimation and some model-fit analysis of multidimensional IRT models," Psychometrika, Springer;The Psychometric Society, vol. 66(4), pages 541-561, December.
    8. McCulloch, Robert & Rossi, Peter E., 1994. "An exact likelihood analysis of the multinomial probit model," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 207-240.
    9. Florin Vaida & Suzette Blanchard, 2005. "Conditional Akaike information for mixed-effects models," Biometrika, Biometrika Trust, vol. 92(2), pages 351-370, June.
    10. Browne, William J., 2006. "MCMC algorithms for constrained variance matrices," Computational Statistics & Data Analysis, Elsevier, vol. 50(7), pages 1655-1677, April.
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    Citations

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    Cited by:

    1. 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.
    2. Xueying Tang & Zhi Wang & Qiwei He & Jingchen Liu & Zhiliang Ying, 2020. "Latent Feature Extraction for Process Data via Multidimensional Scaling," Psychometrika, Springer;The Psychometric Society, vol. 85(2), pages 378-397, June.
    3. Lara Fontanella & Annalina Sarra & Pasquale Valentini & Simone Zio & Sara Fontanella, 2018. "Varying levels of anomie in Europe: a multilevel analysis based on multidimensional IRT models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 102(4), pages 589-610, October.
    4. Di Mascio, Rita & Fatima, Johra, 2018. "The role of identification in frontline employee decision-making," Journal of Retailing and Consumer Services, Elsevier, vol. 43(C), pages 131-138.
    5. Shaw, Amy & Elizondo, Fabian & Wadlington, Patrick L., 2020. "Reasoning, fast and slow: How noncognitive factors may alter the ability-speed relationship," Intelligence, Elsevier, vol. 83(C).
    6. Sun-Joo Cho & Paul Boeck & Susan Embretson & Sophia Rabe-Hesketh, 2014. "Additive Multilevel Item Structure Models with Random Residuals: Item Modeling for Explanation and Item Generation," Psychometrika, Springer;The Psychometric Society, vol. 79(1), pages 84-104, January.
    7. Fang Liu & Xiaojing Wang & Roeland Hancock & Ming-Hui Chen, 2022. "Bayesian Model Assessment for Jointly Modeling Multidimensional Response Data with Application to Computerized Testing," Psychometrika, Springer;The Psychometric Society, vol. 87(4), pages 1290-1317, December.
    8. 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.
    9. Must, Olev & Must, Aasa, 2018. "Speed and the Flynn Effect," Intelligence, Elsevier, vol. 68(C), pages 37-47.
    10. Wim J. van der Linden & Xinhui Xiong, 2013. "Speededness and Adaptive Testing," Journal of Educational and Behavioral Statistics, , vol. 38(4), pages 418-438, August.
    11. Maria Bolsinova & Jesper Tijmstra, 2019. "Modeling Differences Between Response Times of Correct and Incorrect Responses," Psychometrika, Springer;The Psychometric Society, vol. 84(4), pages 1018-1046, December.
    12. Sukaesi Marianti & Jean-Paul Fox & Marianna Avetisyan & Bernard P. Veldkamp & Jesper Tijmstra, 2014. "Testing for Aberrant Behavior in Response Time Modeling," Journal of Educational and Behavioral Statistics, , vol. 39(6), pages 426-451, December.

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    Keywords

    speed; accuracy; IRT; response times;
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