[R] proportional odds model in R

[Michael Dewey]

At 08:51 02/08/2007, Ramon Martínez Coscollà wrote:
>Hi all!!

There is no need to post twice, nor to also post on allstat.

Pages 204-205 of MASS for which this software is 
a support tool provides ample information on how to compare models.

>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
>test?
>
>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.
>
>Thanks.

Michael Dewey
http://www.aghmed.fsnet.co.uk