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Multidimensional and longitudinal item response models for non-ignorable data

Author

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  • Santos, Vera Lúcia F.
  • Moura, Fernando A.S.
  • Andrade, Dalton F.
  • Gonçalves, Kelly C.M.

Abstract

A multidimensional item response approach is proposed to model non-ignorable responses in multiple-choice educational data. The model considers latent traits related to individual proficiency as well as the propensity to answer items. Thus, in addition to modeling the probability of scoring on an item, the probability of answering it is also modeled. Simulation studies are presented to evaluate the efficiency of the estimation procedure in recovering the true values of the model parameters considering several particular cases of the dimensions of proficiency and propensity. The simulation study also compares the proposed approach with others commonly applied in practice. A further extension to cope with longitudinal data with non-ignorable missing item responses is also proposed, together with an application to a Brazilian longitudinal educational evaluation study.

Suggested Citation

  • Santos, Vera Lúcia F. & Moura, Fernando A.S. & Andrade, Dalton F. & Gonçalves, Kelly C.M., 2016. "Multidimensional and longitudinal item response models for non-ignorable data," Computational Statistics & Data Analysis, Elsevier, vol. 103(C), pages 91-110.
    • Handle: RePEc:eee:csdana:v:103:y:2016:i:c:p:91-110
    DOI: 10.1016/j.csda.2016.05.002
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    References listed on IDEAS

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    2. Richard J. Patz & Brian W. Junker, 1999. "Applications and Extensions of MCMC in IRT: Multiple Item Types, Missing Data, and Rated Responses," Journal of Educational and Behavioral Statistics, , vol. 24(4), pages 342-366, December.
    3. 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.
    4. Frederic Lord, 1983. "Maximum likelihood estimation of item response parameters when some responses are omitted," Psychometrika, Springer;The Psychometric Society, vol. 48(3), pages 477-482, September.
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    Cited by:

    1. Robitzsch, Alexander, 2020. "About Still Nonignorable Consequences of (Partially) Ignoring Missing Item Responses in Large-scale Assessment," OSF Preprints hmy45, Center for Open Science.

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