You have a dataset with missing values and you've chosen to use multiple imputation. However, the results after applying multiple imputation are not as expected. What factors might be causing this?

  • Both too few and too many imputations
  • The model used for imputation is perfect
  • Too few imputations
  • Too many imputations
If too few imputations are used in multiple imputation, the results may not be accurate. This may lead to an underestimation of standard errors and incorrect statistical inference. Increasing the number of imputations generally leads to more accurate results.
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