All,
Just a couple of questions after (re-)running some -mlogit- models.
First, after running one such model (modelling party victories at British
by-elections), one of the coefficients returned looked a bit odd:
-----------------------------------------------------
| Robust
bewin | RRR Std. Err. z P>|z|
-------------+---------------------------------------
con |
celtic | 1.96e-17 2.21e-17 -34.21 0.000
The base category against the Conservatives here is Labour. What this is
saying, if I'm interpreting this (quasi-)odds ratio correctly, is that,
after I
. display 1/0.0000000000000000196
5.102e+16
the model is saying that the odds of Labour winning a by-election in
either Scotland or Wales are 51,020,000,000,000,000 times greater than the
Conservatives, Now, I'd certainly expect Labour's odds to be higher in
this region simply because they have been the strongest party there for
many decades, but not quite _this_ high! What to do about this? This model
was estimated along with seven other factors. No more factors could be
added without getting back an -mlogit- model returned with blanks all over
the place.
Second, Dow and Endersby (2004: 117) have recently reported MNL (and MNP)
models together with log_10 hessian condition numbers, which I think would
be useful to report, for the reasons they mention. -search-ing and
-findit- only produced the -hessian- option in -ml-, which isn't what I'm
looking for. Is there a way of reporting these after -mlogit- in Stata
8.2?
Ta.
CLIVE NICHOLAS |t: 0(44)191 222 5969
Politics Building |e: [email protected]
School of Geography, |f: 0(44)870 126 2421
Politics & Sociology |
University of |
Newcastle-upon-Tyne |
Newcastle-upon-Tyne |
NE1 7RU |
United Kingdom |http://www.ncl.ac.uk/geps
Dow JA and Endersby JW (2004) "Multinomial probit and multinomial logit: a
comparison of choice models for voting research", ELECTORAL STUDIES 23(1):
107-22.
*
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