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Re: st: -gologit2- and testing the difference between coefficients
From |
Sara Mottram <[email protected]> |
To |
[email protected] |
Subject |
Re: st: -gologit2- and testing the difference between coefficients |
Date |
Thu, 29 Mar 2007 14:23:09 +0100 |
Dear Herve,
If I understand you correctly, you are fitting a generalised ordered
logit model (i.e. a partial proportional odds model with all variables
non-proportional) and you want to test whether you can assume
proportional odds for your independent variable sales_int.
To do this, I think you need to drop the option v1 to allow proportional
odds for some variables. You can then assess the need for one or two
coefficients in for each independent variable using the option autofit
or through likelihood ratio tests with lrtest.
Richard Williams who wrote this program has a great website, on which he
has a paper on -gologit2- from the Stata Journal. You should definitely
check this out. http://www.nd.edu/~rwilliam/gologit2/index.html
Hope this helps.
Sara
Herve STOLOWY wrote:
Dear Statalisters:
I use the -gologit2- command (downloadable from ssc). Here is my syntax:
xi, prefix(): gologit2 format size1 auditor_d standards_d for_list sales_int instit_for lev2 i.gics4, v1 nolabel
The dependent variable, format is coded 0, 1 or 2. I get two equations and, consequnetly, two panels of results.
I would like to know if is possible to test, for a given variable, if the two coefficients in each equation are different from one another? To be clearer, I have the variable sales_int. In panel 1, the coefficient is 1.314. In panel 2, the coefficient for the same variable is 1.913. Both are significant at the 0.10 level. Is there a way to test that 1.314 is statistically different from 1.913?
Best regards
Herv� Stolowy
***********************************************************
Professeur/Professor
HEC Paris
D�partement Comptabilit� Contr�le de gestion / Dept of Accounting and Management Control
1, rue de la Liberation
78351 - Jouy-en-Josas
France
Tel: +33 1 39 67 94 42 - Fax: +33 1 39 67 70 86
mail: stolowy at hec dot fr
web: http://studies.hec.fr/web/stolowy
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--
Sara Mottram
Research Assistant: Biostatistics
Primary Care Musculoskeletal Research Centre
Primary Care Sciences
Keele University
Staffordshire, ST5 5BG
Tel: 01782 584711
Fax: 01782 583911
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* http://www.ats.ucla.edu/stat/stata/