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RE: st: Test of ordered probit vs ordinary probits
At 06:14 AM 11/1/2007, Schaffer, Mark E wrote:
This takes me back to my original example of a bunch of separate
probits, but this time contrasted with, e.g., the default behavior of
-gologit2- (with link(pr) to make it a generalized ordered probit). The
latter imposes only the constraint that the cutoffs are ordered,
corresponding to order-ability of the outcome variable. How would you
test this constraint?
Actually, an unconstrained gologit doesn't even impose that
constraint. Indeed, Clogg argued that the model isn't ordinal (or at
least need not be ordinal). You can even rearrange the categories of
Y and still get about the same fit! Since unconstrained gologit has
as many parameters as mlogit, this actually isn't that surprising.
This handout talks about possible interpretations of a gologit model:
http://www.nd.edu/~rwilliam/gologit2/RWNASUG2006.pdf
One of the ideas tossed out is that the same Y could be ordinal in
different ways, e.g. it might be ordered Strongly Disagree to
Strongly Agree; or it might be ordered indifferent to feel strongly
(either agree or disagree). For some independent vars, the first
ordering may be appropriate, but for others the 2nd ordering may be
appropriate.
This isn't really answering your question. But, informal checks, I
think, would include looking for sign flips across
equations. Usually, differences in coefficients across equations are
just a matter of degree (e.g. they're all positive but differ in
magnitude) but if you see them changing sign then that suggests the
relationship is not ordinal or perhaps differently-ordinal (i.e. the
var should be coded differently, as I suggest above).
-------------------------------------------
Richard Williams, Notre Dame Dept of Sociology
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