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Ignoring Non-ignorable Missingness

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  • Sophia Rabe-Hesketh

    (University of California, Berkeley)

  • Anders Skrondal

    (Norwegian Institute of Public Health
    University of Oslo
    University of California, Berkeley)

Abstract

The classical missing at random (MAR) assumption, as defined by Rubin (Biometrika 63:581–592, 1976), is often not required for valid inference ignoring the missingness process. Neither are other assumptions sometimes believed to be necessary that result from misunderstandings of MAR. We discuss three strategies that allow us to use standard estimators (i.e., ignore missingness) in cases where missingness is usually considered to be non-ignorable: (1) conditioning on variables, (2) discarding more data, and (3) being protective of parameters.

Suggested Citation

  • Sophia Rabe-Hesketh & Anders Skrondal, 2023. "Ignoring Non-ignorable Missingness," Psychometrika, Springer;The Psychometric Society, vol. 88(1), pages 31-50, March.
    • Handle: RePEc:spr:psycho:v:88:y:2023:i:1:d:10.1007_s11336-022-09895-1
    DOI: 10.1007/s11336-022-09895-1
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    References listed on IDEAS

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