At 12:54 03/04/2008, 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.
For Poisson models and for the negative binomial you have a single outcome, a count. For the binomial you can have two columns of counts of successes and failures (there are other ways of arranging your data). I think you might want to try the beta-binomial which is available I think in aod. However I still think reading the relevant section of MASS first would be a good idea (or some equivalent text). >Wade > >On Thu, Apr 3, 2008 at 7:23 AM, Michael Dewey ><<mailto:[EMAIL PROTECTED]>[EMAIL PROTECTED]> 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>http://www.aghmed.fsnet.co.uk > Michael Dewey http://www.aghmed.fsnet.co.uk ______________________________________________ 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.
