Dear r-sig-ME,
I am working with a small (zero-inflated) dataset of counts. The design is
repeated-measures, with several measures at each time point made in
experimental blocks. I have fit the model with glmmADMB using the
zero-inflated poisson options:
zip<-glmmadmb(wasp~ treatment + (1|sample.period)
+ (1|block), data=data,
family="poisson", zeroInflation=TRUE)
I am suspicious of 1-3 observations (the dataset is only 24 observations
big, so I promise to be cautious), and wish to evaluate their influence on
the model fit. Usually I work in lme4, then use the influence.ME package
and eliminate points based on cook's distance/leverage plots. Applying
influence.ME to the glmmADMB model produces a strange error message:
library(influence.ME)
infl <- influence(zip, obs = TRUE)
Error in eval(expr, envir, enclos) : object 'sample.period' not found
For some reason influence.ME is not finding my random factor
"sample.period." Are glmmADMB and influence.ME incompatible when
zero-inflation models are involved? If anyone knows of an alternative
approach I would love to hear about it.