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Outliers in nutrient intake data for U.S. adults: national health and nutrition examination survey 2017-2018.

Sara BurchamYuki LiuAshley L MerianosAngelico Mendy
Published in: Epidemiologic methods (2023)
This study, the first to use 2017-2018 NHANES dietary data for outlier evaluation, emphasizes the importance of selecting an appropriate decision test considering factors such as statistical power, sample size, normality assumptions, the proportion of data removed, effect estimate changes, and the consistency of estimates across sample sizes. We recommend the use of non-parametric tests for non-normally distributed variables of interest.
Keyphrases
  • electronic health record
  • big data
  • machine learning
  • weight gain
  • artificial intelligence
  • weight loss