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leafminesglm
2006 Apr 23
1
Comparing GLMMs and GLMs with quasi-binomial errors?
...two columns with total number of leaves per seedling and number of
leaves attacked by that herbivory category) - and then compared these models
to GLMs without the random effect.
## model example1: leaf mines GLMM
proportion.leafmines <- cbind(leaves.affected, total.leaves -
leaves.affected)
leafminesGLMM <- glmmPQL(proportion.leafmines ~ PLATEAU * DISTANCE,
random=~1| TreeID, family=binomial(link=logit))
##AIC(leafminesGLMM) = 474.773
## model example2: leaf mines GLM
leafminesGLM <- glm(proportion.leafmines ~ PLATEAU * DISTANCE,
family=binomial(link=logit))
##AIC(leafminesGLM) = 207.94...