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Implementing Multiple Imputation for Missing Data in Longitudinal Studies When Models are Not Feasible: An Example Using the Random Hot Deck Approach.

Chinchin WangTyrel StokesRussell J SteeleNiels WedderkoppIan Shrier
Published in: Clinical epidemiology (2022)
Random hot deck imputation should be considered as an alternative method when model-based approaches are infeasible, specifically where there are constraints within and between covariates.
Keyphrases
  • electronic health record
  • big data
  • quality improvement
  • cross sectional
  • case control
  • neural network
  • machine learning
  • data analysis