That amount of overdispersion would make the use of a poisson model very questionable, and will very likely result in estimated standard errors that are too low, hence the change in statistical significance when you switch to quasipoisson.
On 06/03/07, Cristina Gomes <[EMAIL PROTECTED]> wrote: > Hi all, > I was wondering if somebody could give me advice regarding the > dispersion parameter in GLMM's. I'm a beginner in R and basically in > GLMM's. I've ran a GLMM with a poisson family and got really nice > results that conform with theory, as well with results that I've > obtained previously with other analysis and that others have obtained in > similar studies. But the dispersion parameter is too large (25 compared > to 1). So I ran a quasipoisson that allows for overdispersion and all of > the significant results fell out. My question is, how much does > overdispersion invalidate ones results when using a poisson family? What > could the reason be for having non significant results with a > quasipoisson distribution? > If anybody could give me some help with this or/and recommend me > literature that is somewhat comprehensible to lay people (i.e. non > statisticians) that would be great. > Thanks in advance, > Cristina. > > ______________________________________________ > R-help@stat.math.ethz.ch 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. > -- ================================= David Barron Said Business School University of Oxford Park End Street Oxford OX1 1HP ______________________________________________ R-help@stat.math.ethz.ch 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.