
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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