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Re: st: Treatment for Missing Values - What Options ?


From   Maarten buis <maartenbuis@yahoo.co.uk>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Treatment for Missing Values - What Options ?
Date   Tue, 14 Jul 2009 20:42:11 +0000 (GMT)

--- On Tue, 14/7/09, Chao Yawo wrote:
> So the missing values result from interview errors, and the
> errors are not related to my DV.  In fact, the DV had only
> 161 missing variables.

This is something you can check (assume that rep78 is your 
unsafe sex variable and mpg is your dependent variable ):

*------ begin example ------
sysuse auto, clear
gen mis = missing(rep78)
logit mis mpg
*------- end example -------

>  If I ignore the errors on that single IV then it implies I
> will have to accept the lower N (sample size) my analysis,
> and explain that in my write-up (that changes in sample
> size for the regression result from missing values on some
> of the covariates??

This is very common, look up some leading empirical 
publications in your discipline to see what the most common
formulation in your discipline is. You can do more: you have
reason why your missing data is not related to your dependent
variable, and you checked that, and the Allison reference I 
gave in my previous post explains why your results are not
biased by these missing values.

-- Maarten

-----------------------------------------
Maarten L. Buis
Institut fuer Soziologie
Universitaet Tuebingen
Wilhelmstrasse 36
72074 Tuebingen
Germany

http://home.fsw.vu.nl/m.buis/
-----------------------------------------


      

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