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About Still Nonignorable Consequences of (Partially) Ignoring Missing Item Responses in Large-scale Assessment

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  • Robitzsch, Alexander

Abstract

In recent literature, alternative models for handling missing item responses in large-scale assessments are proposed. In principle, based on simulations and arguments based test theory (Rose, 2013). In those approaches, it is argued that missing item responses should never be scored as incorrect, but rather treated as ignorable (e.g., Pohl et al., 2014). The present contribution shows that these arguments have limited validity and illustrates the consequences in a country comparison in the PIRLS 2011 study. A different treatment of missing item responses than recoding them as incorrect leads to significant changes in country rankings, which induces nonignorable consequences regarding the results' validity. Additionally, two alternative item response models based on different assumptions for missing item responses are proposed.

Suggested Citation

  • Robitzsch, Alexander, 2020. "About Still Nonignorable Consequences of (Partially) Ignoring Missing Item Responses in Large-scale Assessment," OSF Preprints hmy45, Center for Open Science.
    • Handle: RePEc:osf:osfxxx:hmy45
    DOI: 10.31219/osf.io/hmy45
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    References listed on IDEAS

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    1. Norman Rose & Matthias Davier & Benjamin Nagengast, 2017. "Modeling Omitted and Not-Reached Items in IRT Models," Psychometrika, Springer;The Psychometric Society, vol. 82(3), pages 795-819, September.
    2. Frederic Lord, 1974. "Estimation of latent ability and item parameters when there are omitted responses," Psychometrika, Springer;The Psychometric Society, vol. 39(2), pages 247-264, June.
    3. Guillermo Rosas & Yael Shomer & Stephen R. Haptonstahl, 2015. "No News Is News: Nonignorable Nonresponse in Roll‐Call Data Analysis," American Journal of Political Science, John Wiley & Sons, vol. 59(2), pages 511-528, February.
    4. Jung, Hyekyung & Schafer, Joseph L. & Seo, Byungtae, 2011. "A latent class selection model for nonignorably missing data," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 802-812, January.
    5. Paul Holland, 1990. "On the sampling theory roundations of item response theory models," Psychometrika, Springer;The Psychometric Society, vol. 55(4), pages 577-601, December.
    6. 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.
    7. Robert Mislevy, 1991. "Randomization-based inference about latent variables from complex samples," Psychometrika, Springer;The Psychometric Society, vol. 56(2), pages 177-196, June.
    8. Francesco Bartolucci & Giorgio E. Montanari & Silvia Pandolfi, 2018. "Latent Ignorability and Item Selection for Nursing Home Case-Mix Evaluation," Journal of Classification, Springer;The Classification Society, vol. 35(1), pages 172-193, April.
    9. Ofer Harel & Joseph L. Schafer, 2009. "Partial and latent ignorability in missing-data problems," Biometrika, Biometrika Trust, vol. 96(1), pages 37-50.
    10. Jouni Kuha & Myrsini Katsikatsou & Irini Moustaki, 2018. "Latent variable modelling with non‐ignorable item non‐response: multigroup response propensity models for cross‐national analysis," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(4), pages 1169-1192, October.
    11. Thomas Warm, 1989. "Weighted likelihood estimation of ability in item response theory," Psychometrika, Springer;The Psychometric Society, vol. 54(3), pages 427-450, September.
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