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Re: st: how to handle missing observations in a regression model


From   Richard Williams <Richard.A.Williams.5@ND.edu>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: how to handle missing observations in a regression model
Date   Tue, 05 Sep 2006 08:15:36 -0500

At 05:56 AM 9/5/2006, Joseph Coveney wrote:
You can explore the behavior of this approach using -simulate- with a
data-generating process that mimics what you expect prevails in your study.
(This includes the mechanism of missingness.)  A rudimentary example of this
is shown below.  It has 5% randomly missing in both predictors.  The results
indicate that for this approach, compared to just listwise deletion, there
One of the interesting points in Allison's Missing Data book is that, of all the more or less traditional approaches to handling missing data, listwise deletion tends to work as well or better as anything. You have to go to the more recent and advanced techniques if you want to do better.


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Richard Williams, Notre Dame Dept of Sociology
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