[R] FW: Nested and/or crossed and 2 level random factor

Bert Gunter gunter.berton at gene.com
Thu Jul 11 18:47:39 CEST 2013


This is not the best place for this post.

Post instead to r-sig-mixed-models or r-sig-ecology .

Cheers,
Bert

On Thu, Jul 11, 2013 at 8:48 AM, Linda Bürgi <patili_buergi at thotmail.com> wrote:
>
>
>
>
> Dear All,
>
> I have two quick questions about my study design. For 4 years, once every season, we destructively sampled larvae on bushes (the same bushes every time) and measured parasitism on these larvae. We had 10 bushes per location and two locations.
> We are interested in whether parasitism changed over the years and varied with season. With repeated measures on bushes, and bushes nested in location, my model looks like this:
>
> model<-glmmPQL(parasitism ~ year:season + year + season, random=~1|location/bush, family=binomial)
>
> Question 1: A reviewer of our paper suggested that seasons are nested
> within years and that we should include this in the model. However, I
> think seasons are crossed with years, not nested. If that's the case,
> can I leave the model as is (as far as season and years are concerned)?
>
> Question 2: I know it is ridiculous to have location as a random factor since it only has two levels. I've read a lot in the archives and people usually suggest to leave that factor out altogether. But leaving it out is not an option because levels of parasitism
> vary significantly with location (but that is of no interest to us,
> hence not really a fixed factor). Could I just include it as a covariate?  glmmPQL(parasitism ~ year:season + year + season + location, random=~1|bush, family=binomial)?
>
> Thank you already for any answers and suggestions!
>
> PS. I used glmmPQL instead of lmer because without the over-/underdispersion function in lmer everything was highly significant, whereas with glmmPQL it is not.
>
>
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>         [[alternative HTML version deleted]]
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-- 

Bert Gunter
Genentech Nonclinical Biostatistics

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