Ignoring Non-ignorable Missingness

Sophia Rabe-Hesketh and Anders Skrondal
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Anders Skrondal: Norwegian Institute of Public Health

Psychometrika, 2023, vol. 88, issue 1, No 2, 50 pages

Abstract: 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.

Keywords: data deletion; MAR; make-MAR; missing data; m-graph; ordered factorization; protective estimation (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s11336-022-09895-1

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