Re: st: gologit2

[Richard Williams <richardwilliams.ndu@gmail.com>]

Multi-equation methods like mlogit and gologit can estimate a lot of 
parameters, hence things like extreme collinearity may cause more 
grief for them than they do for simpler methods. Having said that, 
multicollinearity is not inherently fatal; you might have problems 
with a small data set and no problems at all if you have 100,000 cases.
I agree with Maarten that you should examine why the multic exists. 
Maybe you have done something stupid, like include a scale along with 
the items used to compute the scale. Conversely, if you have a bunch 
of items that all measure the same concept, you may be able to create 
a single scale out of them that solves your problems.
For more ideas on causes/consequences/possible ways of dealing with 
multicollinearity, see
http://www3.nd.edu/~rwilliam/xsoc63993/l11.pdf

At 08:51 AM 8/28/2013, lan zhang wrote:
> Good morning!
> i want to conduct a gologit2 model, however, the correlations 
> between my independent variables are very high, almost 0.9. Is it 
> still possible for me to use the gologit2 model?
> thanks
> lan
>
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Richard Williams, Notre Dame Dept of Sociology
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