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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--
Brian D. Ripley, rip...@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 272866 (PA)
Oxford OX1 3TG, UK Fax: +44 1865 272595
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