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?
>>    
>>
>
>  
>

	[[alternative HTML version deleted]]


