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st: Stability of gllamm results against linear transformation of independent variables


From   "Hanno Scholtz" <scholtz@soziologie.uzh.ch>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: Stability of gllamm results against linear transformation of independent variables
Date   Thu, 20 Dec 2007 09:36:03 +0100

Hello

I estimate democratization in the European Union's neighborhood as a
function of EU incentives (e.g. whether the EU proposes the chance to get a
member) and some controls. Since democracy (measured by Freedom House) is
stepwise and censored, I use a multinomial probit; since I have panel data
(36 countries and 13 years; for some missings altogether 385 observations),
I need a random effects model. The model includes a time trend. 

The syntax applied is

  gllamm [dependent] year [indepvars], link(oprobit) i([Count variable over
countries])              (1)

After estimating some models, I applied some linear transformations to the
variables, for example

  gen yeart = year - 1990
  gllamm [dependent] yeart [indepvars], link(oprobit) i([Count variable over
countries])             (2)

Much to my surprise I found that the results of (2) deviate from those of
(1) - not only in the coefficient of yeart vs year and the constant, as I
expected, but in every coefficient and z stats. 

Can someone explain me why this is the case? Of course, I studied
Rabe-Hesketh/Skrondal (2005) on the subject, but did not find anything
helpful. Have I overread or misunderstood something? Or is there any
solution I simply do not see? 

Thanks for all help!
Hanno



Rabe-Hesketh, Sophia, and Anders Skrondal (2005): Multilevel and
Longitudinal Modeling Using Stata. College Station: Stata Press

--
Dr. Hanno Scholtz <scholtz@soziologie.uzh.ch>
University of Zurich, Sociological Institute


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