[Rd] Standardized Pearson residuals (and score tests)

[peter dalgaard]

On Mar 16, 2011, at 23:29 , Gordon K Smyth wrote:

> Hi Peter and others,
> 
> If it helps, I wrote a small function glm.scoretest() for the statmod package on CRAN to compute score tests from glm fits.  The score test for adding a covariate, or any set of covariates, can be extracted very neatly from the standard glm output, although you probably already know that.

Thanks Gordon,

I'll have a look. It's the kind of think where you _strongly suspect_ that a neat solution exists, but where you can't just write it down immediately. Looks like your code needs some elaboration to handle factor terms and more general model reductions, though.

-pd

> 
> Regards
> Gordon
> 
> ---------------------------------------------
> Professor Gordon K Smyth,
> NHMRC Senior Research Fellow,
> Bioinformatics Division,
> Walter and Eliza Hall Institute of Medical Research,
> 1G Royal Parade, Parkville, Vic 3052, Australia.
> smyth at wehi.edu.au
> http://www.wehi.edu.au
> http://www.statsci.org/smyth
> 
>> Date: Tue, 15 Mar 2011 12:17:46 +0100
>> From: peter dalgaard <pdalgd at gmail.com>
>> To: Brett Presnell <presnell at stat.ufl.edu>
>> Cc: r-devel at r-project.org
>> Subject: Re: [Rd] Standardized Pearson residuals
>> 
>> 
>> 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.mes at cbs.dk  Priv: PDalgd at gmail.com
> 
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-- 
Peter Dalgaard
Center for Statistics, Copenhagen Business School
Solbjerg Plads 3, 2000 Frederiksberg, Denmark
Phone: (+45)38153501
Email: pd.mes at cbs.dk  Priv: PDalgd at gmail.com