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st: RE: Test for missingness type


From   "Maarten Buis" <M.Buis@fsw.vu.nl>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: RE: Test for missingness type
Date   Wed, 27 Sep 2006 11:51:45 +0200

--- mählmann wrote:
> I have a dataset with one variable (x) partially missing.  I want to
> test if the missingness mechanisms is nonignorable (data is MNAR), ie if
> P(r=1|x,z)  does depend on x, where r is the binary missingness
> indicator and z are completely observed covariates.

Thomas:
Short answer is: "you can't test the MAR/NMAR assumption".

Slightly longer answer is: 
You want to test whether or not x is missing depends on x itself. 
In order to test that you would need to compare the values of x 
when x is observed and the values of x when x is missing. So you
would need to know the values of x when x is missing. If you would 
know that, x wouldn't be missing... So MAR is an untestable 
assumption. 

A common (and in my humble opinion reasonable) way around this
is to assume that missingness on x may depend on lots of other
(fully or partially observed) variables, and assume that after controlling
for these other variables there is nothing left for x itself, i.e. the MAR
becomes more reasonable when you control for more covariates. 

HTH,
Maarten

-----------------------------------------
Maarten L. Buis
Department of Social Research Methodology 
Vrije Universiteit Amsterdam 
Boelelaan 1081 
1081 HV Amsterdam 
The Netherlands

visiting adress:
Buitenveldertselaan 3 (Metropolitan), room Z434 

+31 20 5986715

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



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