 |
[Date Prev][Date Next][Thread Prev][Thread Next][Date index][Thread index]
RE: st: gologit2
At 03:15 PM 4/17/2008, Maarten buis wrote
Alternatives are:
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.
I agree.
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...
Of course, if you want to cheat, you could just run oprobit, and hope
the referees don't realize that oprobit models can have the same
problems as ologit models. You just use more general terminology
such as parallel lines or parallel regressions rather than
proportional odds. I actually had an economist tell me once that
oprobit was better than ologit because only ologit had a problem with
proportional odds. I thought this was kind of silly, because
proportional odds just happens to be a consequence of parallel lines
when using the logit link. Regardless of whether you are using
ologit or oprobit, the method assumes parallel lines.
-------------------------------------------
Richard Williams, Notre Dame Dept of Sociology
OFFICE: (574)631-6668, (574)631-6463
HOME: (574)289-5227
EMAIL: [email protected]
WWW: http://www.nd.edu/~rwilliam
*
* For searches and help try:
* http://www.stata.com/support/faqs/res/findit.html
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/