Re: st: Combine Listwise Deletion and Multiple Imputation?

[Alan Acock <acock@mac.com>]

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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