I'm working with NHIS survye data.  I'd like the to use muliple imputation 
to cover the missing data for the variables in which I'm interested.  My 
question concerns the use of certain variables in the imputation model.  
For example, race would be an important predictor in the imputation 
model, but it has been imputed (hot deck) as have other variables that 
might be useful in the imputation model.  What is the wisdom of using 
data that have been imputed in subsequent imputations models?

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