From: Tom Van Dooren <vdooren_at_rulsfb.leidenuniv.nl>

Date: Thu 20 Oct 2005 - 19:25:51 EST

F test assumes quasibinomial family in: drop1.glm(b1, test = "F")

* > anova(b2,b1,test="F")
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Analysis of Deviance Table

* >
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R-help@stat.math.ethz.ch mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Thu Oct 20 19:34:34 2005

Date: Thu 20 Oct 2005 - 19:25:51 EST

Hi,

I was wondering why anova() and drop1() give different tail
probabilities for F tests.

I guess overdispersion is calculated differently in the following
example, but why?

Thanks for any advice,

Tom

Df Deviance AIC F value Pr(F) <none> 6.3024 10.3024 x 1 6.7301 8.7301 0.2036 0.6824Warning message:

F test assumes quasibinomial family in: drop1.glm(b1, test = "F")

Analysis of Deviance Table

Model 1: y ~ 1

Model 2: y ~ x

Resid. Df Resid. Dev Df Deviance F Pr(>F) 1 4 6.7301 2 3 6.3024 1 0.4277 0.4277 0.5131

R-help@stat.math.ethz.ch mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Thu Oct 20 19:34:34 2005

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