[R] glm deviance question

Prof Brian Ripley ripley at stats.ox.ac.uk
Fri Jan 4 20:47:41 CET 2002


On Fri, 4 Jan 2002, Anne York wrote:

> I am comparing the Splus and R fits of a simple glm.
> In the following, foo is generated from rbinom with size = 20 p = 0.5.
> The coefficients (and SE's0 of the fitted models are the same, but the
> estimated deviances are quite different. Could someone please tell me why
> they are so different? I am using R version 1.3.1 and Splus 2000 release 3
> on windows 2000.

I can't reproduce your S-PLUS results.  I get under 3.4 and 6.0:

Coefficients:
                 Value Std. Error   t value
(Intercept) -0.1502822  0.1002824 -1.498589

    Null Deviance: 26.47916 on 19 degrees of freedom
Residual Deviance: 26.47916 on 19 degrees of freedom

so are you sure you did the same thing?  The coefficients are *not* the
same, BTW (there is a sign change).

>
> ++++++++++++++++++++++
> foo <- c(9,  4, 10,  7, 11, 13,  8,  6, 11, 14, 11,
>          10,  7,  9, 13,  7,  9,  6, 10, 10)
>
> foo.glm <- glm(cbind(foo,20-foo)~1,family=binomial)
>
> In Splus:
>
> summary(foo.glm)
>
> Coefficients:
>                 Value Std. Error  t value
> (Intercept) 0.1502822  0.1002824 1.498589
>
> (Dispersion Parameter for Binomial family taken to be 1 )
>
>     Null Deviance: 21.89527 on 19 degrees of freedom
>
> Residual Deviance: 21.89527 on 19 degrees of freedom
>
>
> In R:
>
> summary(foo.glm)
>
> Coefficients:
>             Estimate Std. Error z value Pr(>|z|)
> (Intercept)  -0.1503     0.1003  -1.499    0.134
>
> (Dispersion parameter for binomial family taken to be 1)
>
>     Null deviance: 26.479  on 19  degrees of freedom
> Residual deviance: 26.479  on 19  degrees of freedom
> AIC: 96.44
>
>
> ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
> Anne E. York
> National Marine Mammal Laboratory
> Seattle WA 98115-0070  USA
> e-mail: anne.york at noaa.gov
> Voice: +1 206-526-4039
> Fax: +1 206-526-6615
> ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
>
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-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272860 (secr)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595

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