Dear Christoph, what command are you using to plot the residuals? If you use the default residuals it will not reflect the variance model. If you use the argument
type="p" then you get the Pearson residuals, which will reflect the weights model. Try something like this: plot(model, resid(., type = "p") ~ fitted(.), abline = 0) I hope that this helps, Andrew On Mon, Jan 24, 2005 at 02:28:44PM +0100, Christoph Scherber wrote: > Dear R users, > > I am currently analyzing a dataset using lme(). The model I use has the > following structure: > > model<-lme(response~Covariate+TreatmentA+TreatmentB,random=~1|Block/Plot,method="ML") > > When I plot the residuals against the fitted values, I see a clear > positive trend (meaning that the variance increases with the mean). > > I tried to solve this issue using weights=varPower(), but it doesn?t > change the residual plot at all. > > How would you implement such a positive trend in the variance? I?ve > tried glmmPQL (which works great with poisson errors), but using glmmPQL > I can?t do model simplification. > > Many thanks for your help! > > Regards > Chris. > > ______________________________________________ > [email protected] mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! > http://www.R-project.org/posting-guide.html -- Andrew Robinson Ph: 208 885 7115 Department of Forest Resources Fa: 208 885 6226 University of Idaho E : [EMAIL PROTECTED] PO Box 441133 W : http://www.uidaho.edu/~andrewr Moscow ID 83843 Or: http://www.biometrics.uidaho.edu No statement above necessarily represents my employer's opinion. ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
