[R-sig-ME] Binomial glmer() with zero-inflated data
jessiebarker at gmail.com
Fri Apr 13 13:39:37 CEST 2018
Dear mixed-model enthusiasts,
I have a question about how to model zero-inflated data (I have several 1's
too, but more 0's).
The data are observations of bees visiting flowers to collect nectar. A
visit can either be "pollination" or "nectar robbing" (the bee collects
nectar from a hole through the side of the flower). Each bee made a
sequence of visits, and the response variable that I am interested in is
how many times a bee robbed nectar. (In many cases a bee did not rob nectar
at all - hence the zero-inflation - and in a few cases it only robbed
nectar.) I observed each bee only once.
The predictor variable I am interested in is the proportion of flowers on
the plant that have holes in them (thus enabling nectar robbing). I have
multiple measurements of the response variable on each plant, but only one
measurement of the predictor variable. So I will include plant as a random
I think I need something like this:
model1 <- glmer ( cbind(rob,pollinate) ~ prop.holes + (1|plant),
But I don't think that can handle the zero-inflation. Does anyone on this
listserv have any advice?
Thanks in advance - I really appreciate any suggestions!
Aarhus Institute of Advanced Studies, Denmark
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