[R] Logistic Regression with 9 classes

Paul Johnson
Mon, 02 Dec 2002 01:43:22 -0000

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