Re: [R] different F test in drop1 and anova

From: Prof Brian Ripley <ripley_at_stats.ox.ac.uk>
Date: Thu 20 Oct 2005 - 21:31:11 EST

On Thu, 20 Oct 2005, Tom Van Dooren wrote:

> 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?

Because of the warning. You are using both inappropriately.

drop1.glm guesses you meant quasibinomial and tells you.

anova.glm guesses you mean the Chisq test (F with infinite denominator df) and does not tell you.

> 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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-- 
Brian D. Ripley,                  ripley@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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Received on Thu Oct 20 21:38:04 2005

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