[R] proportional odds model in R

Ramon Martínez Coscollà ramarcos at gmail.com
Thu Aug 2 09:51:46 CEST 2007

Hi all!!

I am using a proportinal odds model to study some ordered categorical
data. I am trying to predict one ordered categorical variable taking
into account only another categorical variable.

I am using polr from the R MASS library. It seems to work ok, but I'm
still getting familiar and I don't know how to assess goodness of fit.
I have this output, when using response ~ independent variable:

Residual Deviance: 327.0956
AIC: 333.0956
> polr.out$df.residual
[1] 278
> polr.out$edf
[1] 3

When taking out every variable... (i.e., making formula: response ~ 1), I have:

Residual Deviance: 368.2387
AIC: 372.2387

How can I test if the model fits well? How can I check that the
independent variable effectively explains the model? Is there any

Moreover, sendig summary(polr.out) I get this error:

Error in optim(start, fmin, gmin, method = "BFGS", hessian = Hess, ...) :
       initial value in 'vmmin' is not finite

Something to do with the optimitation procedure... but, how can I fix
it? Any help would be greatly appreciated.


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