[R] lme and varFunc()

[Andrew Robinson]

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.
> 
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