AW: st: Binary Variables

["Martin Weiss" <martin.weiss1@gmx.de>]

<> 


" You could check that with a tab region,sum(depvar) command"


Or simply -inspect- the region variable.


HTH
Martin


-----Ursprüngliche Nachricht-----
Von: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von Lachenbruch,
Peter
Gesendet: Mittwoch, 2. Juni 2010 17:51
An: 'statalist@hsphsun2.harvard.edu'
Betreff: RE: st: Binary Variables

It is also possible that some regions are missing.  You could check that
with a tab region,sum(depvar) command

Tony

Peter A. Lachenbruch
Department of Public Health
Oregon State University
Corvallis, OR 97330
Phone: 541-737-3832
FAX: 541-737-4001


-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Natalie Trapp
Sent: Wednesday, June 02, 2010 4:42 AM
To: statalist@hsphsun2.harvard.edu
Subject: Re: st: Binary Variables

Thank you very much.
It is not possible that my dependent variable is constant within a 
region and I want to have the effects
of different regions, so I will try the random effects regression rather 
than aggregating the regions.
Thank you very much once again!

On 6/2/2010 1:20 PM, Nick Cox wrote:
> Another alternative is just to aggregate some regions. If the response is
identical, you lose nothing, except that some thought needs to be given to
the combination of predictor values for those regions. For example, is
population weighting appropriate?


>
> Nick
> n.j.cox@durham.ac.uk
>
> Maarten buis
>
> --- On Wed, 2/6/10, Natalie Trapp wrote:
>    
>> I use a Dummy Variable for 150 regions within the EU27.
>> When I regress the model, I use one region as a reference
>> group, but Stata still automatically omits four to five more
>> regions. Is it maybe because the regions are too similar in
>> their characteristics so that I have to build groups of
>> similar regions? Or is there another way how I can do the
>> regression with all regions of interest?
>>      
> This is a fixed effects regression (assuming you are using
> linear regression, -regress-).  This type of regression can
> only make use of variation within a region, so if the dependent
> variable is constant within a region, the region will be dropped.
> Your alternative is to use random effects regression (see:
> -help xtreg-), but that has disadvantages of its own. It is up
> to you to decide which disadvantages you think are least bad...
>
>
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