[R] glm binomial with no successes

[juli pausas]

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
<ripley at stats.ox.ac.uk> 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
>  >
>  > ______________________________________________
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>  >
>
>  --
>  Brian D. Ripley,                  ripley at 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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