Under-dispersion - a stats question?
On Tue, 2005-10-11 at 17:16 -0400, Kjetil Holuerson wrote:
Martin Henry H. Stevens wrote:
Hello all: I frequently have glm models in which the residual variance is much lower than the residual degrees of freedom (e.g. Res.Dev=30.5, Res.DF = 82). Is it appropriate for me to use a quasipoisson error distribution and test it with an F distribution? It seems to me that I could stand to gain a much-reduced standard error if I let the procedure estimate my dispersion factor (which is what I assume the quasi- distributions do).
I did'nt see an answer to this. maybe you could treat as a quasimodel, but first you should ask why there is underdispersion. Underdispersion could arise if you have dependent responses, for instance, competition (say, between plants) could produce underdispersion. Then you would be better off changing to an appropriate model. maybe you could post more about your experimental setup?
Some ecologists from Bergen, Norway, suggest using quasipoisson with its underdispersed residual error (while I wouldn't do that). However, it indeed would be useful to know a bit more about the setup, like the type of dependent variable. If the dependent variable happens to be the number of species (like it's been in some papers by MHHS), this certainly is *not* Poisson nor quasi-Poisson nor in the exponential family, although it so often is modelled. I've often seen that species richness (number of species -- or in R-speak 'tokens' -- in a collection) is underdispersed to Poisson, and for a good reason. Even there I'd play safe and use poisson() instead of underdispersed quasipoisson(). cheers, jari oksanen
Jari Oksanen -- Dept Biology, Univ Oulu, 90014 Oulu, Finland Ph. +358 8 5531526, cell +358 40 5136529, fax +358 8 5531061 email jari.oksanen at oulu.fi, homepage http://cc.oulu.fi/~jarioksa/