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 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. ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.