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]]
______________________________________________
[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
