[R] Inconsistency in F values from dropterm and anova

[Prof Brian Ripley]

Perhaps if you followed the posting guide and did not send HTML mail 
your tables would be readable.  But your anova call seems wrong, as 
you have the models in decreasing not increasing order.

The correct result is (computing F test by hand)

> 23.1814/93
[1] 0.2492624
> 1.5475/3
[1] 0.5158333
> 0.5158333/0.2492624
[1] 2.069439

so the incorrect use of anova has given you an invalid result 
(although I don't see immediately what it has done)

On Thu, 29 Jan 2009, IMS wrote:

>
> Hi,
>
> I'm working on fitting a glm model to my data using Gamma error structure
> and reciprocal link.  I've been using dropterm (MASS) in the model
> simplification process, but the F values from analysis of deviance tables
> reported by dropterm and anova functions are different - sometimes
> significantly so.  However, the reported residual deviances, degrees of
> freedom, etc. are not different.  I don't know how to calculate F values
> from deviance tables (and can't seem to find anything suggesting how), and
> so haven't been able to calculate F for myself to see which is more
> accurate.  Below is an example of the code, and I'm using R version 2.8.0.
>
>> model1=glm(diff2^(0.491)~mtype*morder,family=Gamma)
>> dropterm(model1,test="F")
> Single term deletions
>
> Model:
> diff2^(0.491) ~ mtype * morder
>                    Df  Deviance     AIC   F value   Pr(F)
>               23.181   -16.813
> mtype:morder  3   24.729   -13.741  2.0694   0.1096
>
>> model2=update(model1,~.-mtype:morder)
>> anova(model1,model2,test="F")
> Analysis of Deviance Table
>
> Model 1: diff2^(0.491) ~ mtype * morder
> Model 2: diff2^(0.491) ~ mtype + morder
>  Resid. Df Resid. Dev Df Deviance      F  Pr(>F)
> 1        93    23.1814
> 2        96    24.7288 -3  -1.5475 3.0241 0.03352 *
> ---
> Signif. codes:  0 ???***??? 0.001 ???**??? 0.01 ???*??? 0.05 ???.??? 0.1 ??? ??? 1
>
> -- 
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> Sent from the R help mailing list archive at Nabble.com.
>
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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)
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