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Re: st: Combine Listwise Deletion and Multiple Imputation?


From   Alan Acock <acock@mac.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Combine Listwise Deletion and Multiple Imputation?
Date   Thu, 11 Aug 2011 17:37:51 -0700

Why not impute all of the variables? Listwise deletion assumes missing values are missing completely at random (MCAR) whereas multiple imputation assumes it is missing at random (MAR), which is a much more reasonable assumption. 
--Alan Acock
On Aug 11, 2011, at Thu Aug6:43 , Andrea Bennett wrote:

> Hi!
> 
> I am dealing with a data set (field experiment) containing missing values. I wonder, is it ok to combine both methods, that is "Listwise Deletion" and "Multiple Imputation" in order to deal with missing values?
> 
> I've been reading Paul D. Allison's "Missing Data" and cannot find a clear answer there. I want combine both methods because the loss in observations is small except for one particular variable where I have lots of "don't know" answers (question: highest completed education of parents). I would then only apply MI for one variable where Listwise Deletion would result in quite a severe loss.
> 
> Does anyone of you, who is more familiar with MI, disagree in general? Do you recommend reading a specific book, potentially tailored to Stata users?
> 
> Many thanks in advance,
> 
> Andrea
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