How to replace missing data points with Multiple Imputation Data Sets

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How to replace missing data points with Multiple Imputation Data Sets

mohsin99
Hello all,
I have successfully imputed 20 data sets using SPSS 20 Multiple Imputation; and have got pooled estimates of mean, SD, SE, variance etc. However, I am still unable identify that how to replace empty/missing data points in original data set? Do I need to take average of each imputed data point (which originally was missing in original data set) from all imputed data sets to replace it in original data set ?
I will thankful if anyone can help me out.
Regards
Mohsin
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Re: How to replace missing data points with Multiple Imputation Data Sets

Bruce Weaver
Administrator
There is no replacement of missing data points in the original data set.  MI works exactly the way you've described:  I.e., the analysis (whatever it is) is done on each of the imputed data sets, and the results are pooled (using the method described by Rubin).  


mohsin99 wrote
Hello all,
I have successfully imputed 20 data sets using SPSS 20 Multiple Imputation; and have got pooled estimates of mean, SD, SE, variance etc. However, I am still unable identify that how to replace empty/missing data points in original data set? Do I need to take average of each imputed data point (which originally was missing in original data set) from all imputed data sets to replace it in original data set ?
I will thankful if anyone can help me out.
Regards
Mohsin
--
Bruce Weaver
bweaver@lakeheadu.ca
http://sites.google.com/a/lakeheadu.ca/bweaver/

"When all else fails, RTFM."

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Re: How to replace missing data points with Multiple Imputation Data Sets

Jon K Peck
In reply to this post by mohsin99
As Bruce said, the nature of multiple imputation is that there is no single replacement for a missing data point.  That is why the dataset is replicated several times (20 is really a lot!).  If you want a single imputed value, you can use the MVA procedure, but that collapses the distribution of missing values to a single point, so you lose the uncertainty that the multiple imputation process retains.


Jon Peck (no "h") aka Kim
Senior Software Engineer, IBM
[hidden email]
phone: 720-342-5621




From:        mohsin99 <[hidden email]>
To:        [hidden email],
Date:        05/14/2013 05:52 PM
Subject:        [SPSSX-L] How to replace missing data points with Multiple              Imputation Data              Sets
Sent by:        "SPSSX(r) Discussion" <[hidden email]>




Hello all,
I have successfully imputed 20 data sets using SPSS 20 Multiple Imputation;
and have got pooled estimates of mean, SD, SE, variance etc. However, I am
still unable identify that how to replace empty/missing data points in
original data set? Do I need to take average of each imputed data point
(which originally was missing in original data set) from all imputed data
sets to replace it in original data set ?
I will thankful if anyone can help me out.
Regards
Mohsin



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Re: How to replace missing data points with Multiple Imputation Data Sets

mohsin99
In reply to this post by mohsin99
Thanks Bruce and Jhon. Now, I got the whole idea.
Thanks again.