What is a primary assumption when using regression imputation?

  • All data is normally distributed
  • Missing data is missing completely at random (MCAR)
  • Missing values are negligible
  • The relationship between variables is linear
A primary assumption when using regression imputation is that the relationship between variables is linear. This is because regression imputation uses a regression model to predict missing values, and the basic form of regression models assumes a linear relationship between predictor and response variables.
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