First define what you mean by residuals. Then extract them. Then use qqnorm and qqline as usual.
Note that the first step is not clearcut even for a binomial glm, nor for a Gaussian mixed-effects model. On Thu, 4 Mar 2004, Christoph Scherber wrote: > Thanks! > > And how can I then plot a Q-Q line for model checking? qqnorm works > fine, but I couldn�t find how to use qqline for mixed effects models of > this type > > so far, I have tried (e.g.) > > qqnorm(glm1,~resid(.)|TREATMENT) > > but I don�t know how to specify qqline for this > > the full model is > glm1_glmmPQL(cbindarea~BLOCK+targetweight+TREATMENT+SOWNDIV+GRASS+LEG+SHERB+THERB,random=~1|PLOTCODE/TREATMENT,family=binomial) > > where categorical variables are in capital letters > > Best regards, > Chris. > > > Prof Brian Ripley wrote: > > >There are several possibilities, including glmmPQL (MASS) and GLMM (lme4). > >Be careful with the interpretation, as you don't have the advantages of > >balance that the classical AoV gives you. > > > >On Thu, 4 Mar 2004, Christoph Scherber wrote: > > > > > > > >>I have proportion data with binomial errors. The problem is that the > >>whole experiment was laid out as a split-plot design. > >> > >>Ideally, what I would like is having a glm with an Error term such as > >>glm(y~x+Error(A/B)) but I fear this is not possible. Would using lme be > >>an alternative? How could I state the variance structure, then? > >> > >> > > > > > > > -- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UK Fax: +44 1865 272595 ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
