Thank you very much for your reply.
Then I understand that would not be correct to perform the test in
summary for testing the significance of the different levels of a
factor in relation to the first level, including when there are more
than 2 levels, as in my real case; at least for binomial regressions.
So here a more close-to-real example, with a 3-level factor
s <- c(rpois(8, 4), rep(0, 4))
f <- rpois(12, 30)
tr <- gl(3, 4)
sf <- cbind(s,f)
drop1(glm(sf ~ tr, family="binomial"), test="Chisq") # significant
summary(glm(sf ~ tr, family="binomial")) # the 3rd level
is not significant from the 1st
So I understand that I need to explite the data and perform the two
tests separately:
drop1(glm(sf ~ tr, family="binomial", subset=(tr %in% c("1", "2"))),
test="Chisq") # ns as expected
drop1(glm(sf ~ tr, family="binomial", subset=(tr %in% c("1", "3"))),
test="Chisq") # significant, as expected
Is this the correct approach?
Many thanks
Juli
On Wed, Feb 27, 2008 at 12:13 PM, Prof Brian Ripley
<[EMAIL PROTECTED]> wrote:
> On Wed, 27 Feb 2008, juli pausas wrote:
>
> > Dear all,
> > I have a question on glm, family binomial. I do not see significant
> > differences between the levels of a factor (treatment) if all data for
> > a level is 0; and replacing a 0 for a 1 (in fact reducing the
> > difference), then I detect the significant difference that I expected.
>
> This is because you are using the wrong test, one with negligible power.
> See MASS4 pp.197-8 -- you need to use the LRT, as in
>
> > drop1(glm(sf ~ tr, family="binomial"), test="Chisq")
> Single term deletions
>
> Model:
> sf ~ tr
> Df Deviance AIC LRT Pr(Chi)
> <none> 1.595 17.730
> tr 1 24.244 38.379 22.649 1.944e-06
>
> (and in your example you can replace 'drop1' by 'anova').
>
>
> > Is there a way to overcome this problem? or this is an expected
> > behaviour ? Here is an example:
> >
> > s <- c(2,4,4,5,0,0,0,0)
> > f <- c(31,28,28,28,32,37,34,35)
> > tr <- gl(2, 4)
> > sf <- cbind(s,f) # numbers of successes and failures
> > summary(glm(sf ~ tr, family="binomial")) # tr ns
> >
> > sf[8,1] <- 1
> > summary(glm(sf ~ tr, family="binomial")) # tr significative **
> >
> > Thanks for any suggestion
> >
> > Juli
> >
> > --
> > http://www.ceam.es/pausas
> >
> > ______________________________________________
> > R-help@r-project.org mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> > and provide commented, minimal, self-contained, reproducible code.
> >
>
> --
> Brian D. Ripley, [EMAIL PROTECTED]
> 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
>
--
http://www.ceam.es/pausas
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