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Grade of Membership Response Time Model for Detecting Guessing Behaviors

Author

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  • Artur Pokropek

    (The Institute of Philosophy and Sociology, Polish Academy of Sciences)

Abstract

A response model that is able to detect guessing behaviors and produce unbiased estimates in low-stake conditions using timing information is proposed. The model is a special case of the grade of membership model in which responses are modeled as partial members of a class that is affected by motivation and a class that responds only according to the level of ability. Monte Carlo simulations were conducted to compare the proposed model with an approach that ignored guessing and an approach based on item filtering. In each simulated condition, the proposed model outperformed the other approaches by showing the lowest level of bias and the highest precision of item and persons estimates. Finally, the model was estimated using real life data from Programme for the International Assessment of Adult Competencies research (PIAAC). The results showed slight but expected corrections for the levels of proficiency in all countries.

Suggested Citation

  • Artur Pokropek, 2016. "Grade of Membership Response Time Model for Detecting Guessing Behaviors," Journal of Educational and Behavioral Statistics, , vol. 41(3), pages 300-325, June.
    • Handle: RePEc:sae:jedbes:v:41:y:2016:i:3:p:300-325
    DOI: 10.3102/1076998616636618
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    References listed on IDEAS

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    1. Robert Mislevy & Norman Verhelst, 1990. "Modeling item responses when different subjects employ different solution strategies," Psychometrika, Springer;The Psychometric Society, vol. 55(2), pages 195-215, June.
    2. Elena Erosheva, 2005. "Comparing Latent Structures of the Grade of Membership, Rasch, and Latent Class Models," Psychometrika, Springer;The Psychometric Society, vol. 70(4), pages 619-628, December.
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