[R] Logistic Regression with 9 classes

[Paul Johnson]

Hope this helps:

Your approach depends on your statistical theory.

If the 9 categories are ordered, the ordinal logistic (or probit) model 
is called for.  The first publication I know of that proposed it was R D 
McKelvey and W Zavoina.   A statistical model for the analysis of 
ordinal level dependent variables.Journal of Mathematical Sociology, 
4:103-120, 1975.

The idea is that the probability of falling into one category depends on
z=XB+e,
where e is either logistic or Normal, depending on your taste. THe 
resulting estimates give you estimates of B as well as 8 "thresholds" 
which divide the "z scale" into sections and relate to the predicted 
outcome for the categories.

For that, the MASS packages has polr.


If the 9 categories are unordered, then some other statistical model 
altogether is needed. One I know of is often called a multinomial model, 
where you set one category as the baseline and then estimate the impact 
of the variables to differentiate them from the baseline.  For 9 
cagegories, you'd end up with 8 models, of the sort

ln(Pj/P0) = Xbj, j=1,...8.

In MASS, the function multinom is for that purpose, but I have not tried it.

Luis Silva wrote:
> Hello!
> 
> I need to classify a data set with 19 variables and 9 classes 
> using Logistic Regression(on R).
> I know that when we have only 2 classes we can use glm() to 
> estimate the coefficients of the model. But I don´t understand 
> how can I do a classification task with Logistic Regression on 
> a data set with 9 classes! 
> Does anybody know how can I estimate these coefficients (of a 
> model with 9 classes) on R?
> 
> Thank you!
> Janete
>


-- 
Paul E. Johnson                       email: pauljohn at ukans.edu
Dept. of Political Science            http://lark.cc.ku.edu/~pauljohn
University of Kansas                  Office: (785) 864-9086
Lawrence, Kansas 66045                FAX: (785) 864-5700

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