Good afternoon;



A non-R specific question about mixed models, but I am sending this email
with the hope that others in this group may be familiar with zero-altered
(i.e. zero-inflated or hurdle) models in a mixed model context.



My current project is focused on understanding changes in wetland biota
related to environmental change, and I’m using zero-altered negative
binomial models (implemented in SAS) to evaluate changes in abundance of
invertebrates in these habitats.  I have had good success implementing
models that accurately reflect my data structure and that include predictor
variables of interest, but I do have a question or two outstanding.



Specifically, I am curious about the logit (zero) part of the ZINB mixed
models.  If parameters for this part of the model are estimated imprecisely
and thereby uninformative, should they be removed from the model?



Prior to model construction, I plotted the proportion of zeroes in the
dataset as a function of several variables, and these plots suggested that
wetland class had an important influence on whether or not excess zeroes
were observed.  However, none of the parameter estimates for the wetland
class variable are predicted with any precision (nor is the intercept for
this logit model) in the model that includes them.



If anyone on this list is willing / able to provide any insights or
suggestions as to the mathematical interpretation for the inflation
probability portion of these models, I would be most grateful.



Thank you in advance.



kbg





-~-~-~-
Kirsty E. B. Gurney, Ph.D.
Alaska Cooperative Fish and Wildlife Research Unit
Institute of Arctic Biology
216 Irving 1 Building
University of Alaska Fairbanks
Fairbanks, AK 99775
T: (907) 474 - 7738
-~-~-~-

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