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RE: st: simple question


From   "Nick Cox" <n.j.cox@durham.ac.uk>
To   <statalist@hsphsun2.harvard.edu>
Subject   RE: st: simple question
Date   Wed, 2 Jun 2004 21:29:38 +0100

See also a thread about six weeks ago, especially 
Richard Goldstein's posting on 16 April. 

Nick 
n.j.cox@durham.ac.uk 

Trudy Ann Cameron
 
> You can create a dummy variable for "have_variable" that 
> takes a value of 1
> if the data are non-missing and zero otherwise.  Then you can 
> interact this
> variable with the continuous variable.  The slope that you 
> estimate on the
> interaction with the continuous variable is a slope CONDITIONAL on the
> availability of data for that variable.  The coefficient on the dummy
> variable is the difference in the expected value of Y 
> according to whether
> the data on your continuous variable is missing or not.
> 
> There is not much you can do if the continuous variable is 
> your dependent
> variable, unless you know that 99999 is a top-coded variable, 
> or something
> like that.
> 
> The alternative is to estimate a selection correction model using the
> "have_variable" dummy as the selection variable, and to 
> correct the "main"
> regression for any selection bias.
> 
> Trudy
> 
> At 12:17 PM 6/2/2004, you wrote:
> >Hi, I have continuous variables that are coded 99999 or 
> 77777 for unknown
> >or refused to answer. How do I handle this? I don't want to 
> treat them as
> >missing, if possible.

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