That is exactly how I am writing it.  Glm works fine, but as I stated the
residual deviance is much greater (10x) than the degrees of freedom.  I want
to take a look at using the negative binomial distribution, but I can't get
glm.nb to work. I get the message Error: (subscript) logical subscript too
long.  I have used traceback() and it seems to be in the glm.fitter
function, but as I say I am at the limit of my abilities here.

Wade

On Thu, Apr 3, 2008 at 7:23 AM, Michael Dewey <info@aghmed.fsnet.co.uk>
wrote:

> At 17:03 02/04/2008, Wade Wall wrote:
>
> > Hi all,
> >
> > I have count data (number of flowering individuals plus total number of
> > individuals) across 24 sites and 3 treatments (time since last burn).
> > Following recommendations in the R Book, I used a glm with the model y~
> > burn, with y being two columns (flowering, not flowering) and burn the
> > time
> > (category) since burn.  However, the residual deviance is roughly 10
> > times
> > the number of degrees of freedom, and using the quasibinomial
> > distribution
> > doesn't change this.  Any suggestions as to why the quasibinomial
> > distribution doesn't change the residual deviance and how I should
> > proceed.
> > I know that this level of residual deviance is unacceptable, but not
> > sure is
> > transformations are in order.
> >
>
> You have received much helpful advice from Gavin and Achim and others but
> I wonder whether they are answering the quaestion in your title rather than
> in your post.
>
> Are you doing something like
> fit <- glm(cbind(flower, notflower) ~ burn, family = binomial)
>
> You might find it helpful to read the relevant section in MASS (see
> quasibinomial in the index) or in some other text.
>
>
>  Needless to say that I am at the outer limits of my statistical
> > knowledge.
> >
> > Thanks for any help,
> >
> > Wade Wall
> >
> >        [[alternative HTML version deleted]]
> >
>
> Michael Dewey
> http://www.aghmed.fsnet.co.uk
>
>

	[[alternative HTML version deleted]]

