GLM mixed model with quasibinomial family
Thanks to all of you! I did know the e-mail by Bates, which is out of my understanding, but I did not know the wiki on mixed models and the manuscript by Bolker! My data are based on 2 temporal samples from 8 different sites. I use mixed models because I want to avoid pseudo-replication including the grouping factor into my model and thus looking for the trends within each group and not looking at the data as if they were independent. The question is, can I really use a mixed model if I only have two cases per group? At the end there are 16 cases in the regression plot but I am not sure if such a grouped analysis is right! Thank you again for your help! Javier On Wed, Jul 28, 2010 at 6:44 PM, Javier Martinez
<javi.martinez.lopez at gmail.com> wrote:
Dear R-users, I am using the 'lmer' function from package 'lme4', looking for a regression model which takes into account the grouped nature of my data. I am using frequencies as the dependent variable and percentages as the independent one. After some reading I think I should use the 'quasibinomial' family because there is 'overdispersion' in my data set (greater residual deviance than residual degrees of freedom). So, I test this regression model but I do not get a significance p-value for the regression! I have to test many different regressions with different data, so how can I assess the significance of each of of them? Thank you very much for your help! Javier