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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 06:41:13 -0500

At 03:32 AM 9/5/2006, Simo Hansen wrote:
Dear All;
I am using moter's years of schooling and father's years of schooling as
explanatory variables in my regression model. I also creata a dummy
indicators for whether mother's and father's years of schooling are missing,
respectively:
gen misdaded=dadedec==.
gen mismoted=moteduc==.
When I run the following regression:
reg childedyrs dadeduc moteduc misdaded mismoted,
Stata drops two dummy indicators for whether parents' schooling is missing.
Do you have any suggestion on how I can properly control for whether
mother's and father's years of schooling are missing in my regression model.
Did you also do something like assign the mean to the missing cases on dadeduc and moteduc? If not, all the missing cases are still getting dropped, and dadeduc and moteduc then get dropped because they always equal 0 (non-missing) for the cases being analyzed.

The technique that I think you are using is discussed (along with Stata commands) on pp. 5-6 & 10-12 of the following handout:

http://www.nd.edu/~rwilliam/stats2/l12.pdf

HOWEVER, note that the approach, while once popular, has come to be discredited; as Allison points out in his Sage book "Missing Data", "the method generally produces biased estimates of the coefficients."


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Richard Williams, Notre Dame Dept of Sociology
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