On Mar 15, 2011, at 04:40 , Brett Presnell wrote:
>
>>> Background: I'm currently teaching an undergrad/grad-service course from
>>> Agresti's "Introduction to Categorical Data Analysis (2nd edn)" and
>>> deviance residuals are not used in the text. For now I'll just provide
>>> the students with a simple function to use, but I prefer to use R's
>>> native capabilities whenever possible.
>>
>> Incidentally, chisq.test will have a stdres component in 2.13.0 for
>> much the same reason.
>
> Thank you. That's one more thing I won't have to provide code for
> anymore. Coincidentally, Agresti mentioned this to me a week or two ago
> as something that he felt was missing, so that's at least two people who
> will be happy to see this added.
>
And of course, I was teaching a course based on Agresti & Franklin:
"Statistics, The Art and Science of Learning from Data", when I realized that R
was missing standardized residuals.
> It would also be nice for teaching purposes if glm or summary.glm had a
> "pearsonchisq" component and a corresponding extractor function, but I
> can imagine that there might be arguments against it that haven't
> occured to me. Plus, I doubt that anyone wants to touch glm unless it's
> to repair a bug. If I'm wrong about all that though, ...
>
Hmm, how would that work? If there was one, I'd worry that people would start
subtracting them which is usually not the right thing to do. I do miss having a
test on the residual deviance occasionally (even though it is only sometimes
meaningful), having to fit a saturated model explicitly can be a bit silly.
E.g. in this case (homogeneity of birth rates):
> anova(glm(births~month,poisson,data=bb), test="Chisq")
...
Df Deviance Resid. Df Resid. Dev P(>|Chi|)
NULL 11 225.98
month 11 225.98 0 0.00 < 2.2e-16 ***
> anova(glm(births~1,poisson,data=bb), test="Chisq")
...
Df Deviance Resid. Df Resid. Dev P(>|Chi|)
NULL 11 225.98
Notice that the latter version gives me the correct deviance but no p-value.
A better support for generic score tests could be desirable too. I suspect that
this would actually be the Pearson Chi-square in the interesting cases.
--
Peter Dalgaard
Center for Statistics, Copenhagen Business School
Solbjerg Plads 3, 2000 Frederiksberg, Denmark
Phone: (+45)38153501
Email: pd....@cbs.dk Priv: pda...@gmail.com
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