[R-sig-eco] best choice of GLMM for seed set data

[Mariano Devoto]

Dear all. I am analysing data from a field experiment on a crop
pollination. I want to test if there are differences in the number of seeds
per fruit between three treatments. The experimental design consists of
four separate sites where small subplots (ca. 5 plants each) received one
of the treatments. In each site, 8 subplots were allocated to treatment A,
8 to treatment B and 4 to treatment C. When fruits were ripe I collected
all plants from each subplot and counted stems, fruits per stem and seeds
per fruit. I think a GLMM is the best way to go as I expect random effects
related to field and subplot identity, and my response variable (number of
seeds) is clearly non-normal. My main concern is the choice of the error
family. As I’m counting seeds I first though of a Poisson model, but then
realized that seed numbers only range from 0 to 4. I am now considering
using a binomial model such as this:


glmer(cbind(seeds,4) ~ treatment + (1|site) + (1|subplot), data=seed.data,
family=binomial)


Does this make sense?


I would welcome any advice before hitting “SEND” in Tinn-R :-).



-- 
*Mariano Devoto*

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