Re: [R] dispersion_parameter_GLMM's
I agree with David. A dispersion parameter of 25 suggests that you have mainly 0's in your data set and your model is not adequate. Perhabs you should dichotomize your data in 0 and 1's and use a logistic mixed model but be aware of small numbers of events. 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. O -- View this message in context: http://www.nabble.com/dispersion_parameter_GLMM%27s-tf3354683.html#a11810939 Sent from the R help mailing list archive at Nabble.com. __ 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.
[R] dispersion_parameter_GLMM's
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.
Re: [R] dispersion_parameter_GLMM's
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.
