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RE: st: gologit2
Maarten buis <email@example.com>
RE: st: gologit2
Thu, 17 Apr 2008 21:15:14 +0100 (BST)
--- David Jacobs <firstname.lastname@example.org> wrote:
> > I don't yet find a solution for how to handle referees who often
> > can be mechanical and rigid about the departures they will allow
> > from the most conservative textbook practices.
--- Maarten buis <email@example.com> wrote:
> The easiest way to make everybody happy when the Brant test rejects
> the null, is to show an ologit and a gologit, and (hopefully) show
> that the results are very similar. Then you can refer to the
> distinction between statistical and practical significance, or the
> conclusion does not change, etc.
o If your dataset is large you can use (Raftery 1995), he does not deal
with -ologit- specificaly, but more generally with hypothesis
testing/model selection in large datasets. Than you can compare BICs,
these are less likely to reject the proporitonal odds assumption, and
if they do show strong evidence against the proportional odds
assumption you should probably be worried anyhow.
o You can use other methods for dealing with ordinal dependent
variables that are not surrounded by these ingrained practices, for
instance the stereotyped ordered logit (-slogit- in Stata). This is a
cheat, but if it gets you around the referees...
Raftery, Adrian E. (1995). Bayesian model selection in social research
(with Discussion). Sociological Methodology, 25, 111-196.
Maarten L. Buis
Department of Social Research Methodology
Vrije Universiteit Amsterdam
1081 HV Amsterdam
Buitenveldertselaan 3 (Metropolitan), room Z434
+31 20 5986715
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