Hi Mouna, 

The point of having multiple imputations is to represent the uncertainty about the missing values. Some of the imputations will be close to the truth, others will be far, but this variance is an honest representation of our uncertainty over where the truth is. You definitely want to keep those. You also don't want to combine things from different imputations since that would make them no longer draws from the posterior of the missing data. 

Cheers,
Matt

On Thu, Sep 18, 2014 at 8:09 AM, mouna kessentini <kessentini_mouna@yahoo.fr> wrote:
Dear professors,

I have performed multiple imputation for panel data with Amelia II. After 10 iterations, I noticed that the imputed data concerning for example my variable « X1 » is better after the imputation number 4. However, the imputed data concerning the variable « X2 » is better after the imputation number 2. 
Is it possible to compare the imputed data for every variable in each iteration and retain the best result knowing that the comparison criteria for the best result is the mean value for each variable before and after imputation? Thank you in advance for your answer.
 


Best regards,
Mouna kessentini
 


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