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Re: st: Problem with xi (Stata 11)


From   Roger Newson <r.newson@imperial.ac.uk>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   Re: st: Problem with xi (Stata 11)
Date   Wed, 2 Jun 2010 14:00:59 +0100

I don't know what exactly is going on in your case. However, I do know that Stata 11 users are encouraged officially to use factor variables instead of -xi-, although -xi- should still work (and has done so for me so far).

Best wishes

Roger


Roger B Newson BSc MSc DPhil
Lecturer in Medical Statistics
Respiratory Epidemiology and Public Health Group
National Heart and Lung Institute
Imperial College London
Royal Brompton Campus
Room 33, Emmanuel Kaye Building
1B Manresa Road
London SW3 6LR
UNITED KINGDOM
Tel: +44 (0)20 7352 8121 ext 3381
Fax: +44 (0)20 7351 8322
Email: r.newson@imperial.ac.uk
Web page: http://www.imperial.ac.uk/nhli/r.newson/
Departmental Web page:
http://www1.imperial.ac.uk/medicine/about/divisions/nhli/respiration/popgenetics/reph/

Opinions expressed are those of the author, not of the institution.

On 02/06/2010 13:47, Walter Garcia-Fontes wrote:
I have a problem with the "xi" command in Stata 11 (completely updated
as of today). I tried to create a dataset as simple as possible to
reproduce the problem, which can be accessed from my server. In the
dataset there is a single variable called COUNTRY with numeric codes
for each country and labels identifying the country.

There are 12 different values for COUNTRY (12 different countries) and
79155 observations with a variable number of observations for each country.
To reproduce:

webuse set http://puna.upf.edu
webuse data/data.dta
xi i.COUNTRY

Stata creates variables _ICOUNTRY_n as it should, where n are the
different codes for the 12 countries, omitting the country with the
smallest code.

The problem is that some of the values of _ICOUNTRY are 0 when they
shouldn't be, for instance I have cases where _ICOUNTRY_56 = 0 but
COUNTRY = 56. This happens randomly for a few cases and I've looked at
it from all angles but couldn't figure out what is going on.

If I reduce the number of variables or the number of observations the
problem  disappears at some point, can't tell exactly when, so I'm
providing the smallest example I could build.

Walter

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