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Re: st: Gof for ologit/oprobit


From   n j cox <n.j.cox@durham.ac.uk>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Gof for ologit/oprobit
Date   Wed, 31 Oct 2007 10:10:40 +0000

To add a detail on scatter plots: Ties can be common in this context
and so jittering, or sunflower plots, might be a good idea.

n j cox wrote:

Nobody put in a word for graphical assessment. Scientists like
observed vs fitted plots (calibration plots). Statistically-minded
people usually start with residual vs fitted plots as a health check.
(No news is good news.) It's true, unfortunately, that many of these plots are more difficult to define, or to work with, for discrete response models. It's also true, unfortunately, that StataCorp provided various graphical add-ons for use after -regress- and -anova- but stopped about there. In the Stata Journal in 2004 I wrote up a -modeldiag- package, but it doesn't really extend to ordered logit or ordered probit because of the multiple outcomes. (-findit modeldiag- for locations.) So, that just added a task to my to-do list.

For ordered *it, I'd want first a cross-plot of observed and predicted
outcomes.

Here is a dopey example with Stata 8.2.

. sysuse auto, clear
. ologit rep78 mpg
. predict predicted, xb
. scatter rep78 predicted

Naturally, you might also want to round the predictions. -tabplot-
from SSC then provides a way of keeping the comparison graphical.
It's possible to add an R^2, naturally, but not necessarily useful.
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