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A Case Study of Nonresponse Bias Analysis in Educational Assessment Surveys

Author

Listed:
  • Yajuan Si
  • Roderick J. A. Little

    (University of Michigan)

  • Ya Mo

    (Boise State University)

  • Nell Sedransk

    (National Institute of Statistical Sciences)

Abstract

Nonresponse bias is a widely prevalent problem for data on education. We develop a ten-step exemplar to guide nonresponse bias analysis (NRBA) in cross-sectional studies and apply these steps to the Early Childhood Longitudinal Study, Kindergarten Class of 2010–2011. A key step is the construction of indices of nonresponse bias based on proxy pattern-mixture models for survey variables of interest. A novel feature is to characterize the strength of evidence about nonresponse bias contained in these indices, based on the strength of the relationship between the characteristics in the nonresponse adjustment and the key survey variables. Our NRBA improves the existing methods by incorporating both missing at random and missing not at random mechanisms, and all analyses can be done straightforwardly with standard statistical software.

Suggested Citation

  • Yajuan Si & Roderick J. A. Little & Ya Mo & Nell Sedransk, 2023. "A Case Study of Nonresponse Bias Analysis in Educational Assessment Surveys," Journal of Educational and Behavioral Statistics, , vol. 48(3), pages 271-295, June.
    • Handle: RePEc:sae:jedbes:v:48:y:2023:i:3:p:271-295
    DOI: 10.3102/10769986221141074
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    References listed on IDEAS

    as
    1. Yucel, Recai M., 2011. "State of the Multiple Imputation Software," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 45(i01).
    2. Si, Yajuan & Reiter, Jerome P. & Hillygus, D. Sunshine, 2015. "Semi-parametric Selection Models for Potentially Non-ignorable Attrition in Panel Studies with Refreshment Samples," Political Analysis, Cambridge University Press, vol. 23(1), pages 92-112, January.
    3. repec:mpr:mprres:4780 is not listed on IDEAS
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