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Multiple imputation with missing indicators as proxies for unmeasured variables: simulation study.

Matthew SperrinGlen P Martin
Published in: BMC medical research methodology (2020)
In the presence of missing data, careful use of missing indicators, combined with multiple imputation, can improve causal effect estimation when missingness is informative, and is not detrimental when missingness is at random.
Keyphrases
  • big data
  • machine learning