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Re: st: gologit2


From   Richard Williams <[email protected]>
To   [email protected], "[email protected]" <[email protected]>
Subject   Re: st: gologit2
Date   Wed, 28 Aug 2013 22:37:05 -0500

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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