[R] different F test in drop1 and anova

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

For example:

> x<-c(2,3,4,5,6)
> y<-c(0,1,0,0,1)
> b1<-glm(y~x,binomial)
> b2<-glm(y~1,binomial)
> drop1(b1,test="F")

Single term deletions

Model:
y ~ x

       Df Deviance     AIC F value  Pr(F)
<none>      6.3024 10.3024              
x       1   6.7301  8.7301  0.2036 0.6824
Warning message:
F test assumes quasibinomial family in: drop1.glm(b1, test = "F")
> anova(b2,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

>


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