[R] Overdispersion in count data

Prof Brian Ripley ripley at stats.ox.ac.uk
Thu Apr 3 14:28:13 CEST 2008

On Thu, 3 Apr 2008, Wade Wall wrote:

> 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.

But we can only help you debug this if we have a reproducible example.

> Wade
> On Thu, Apr 3, 2008 at 7:23 AM, Michael Dewey <info at 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]]
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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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