Not an easy fix.  A quick look at github doesn't even drag up any R packages that fit zero-inflated binomials AND hierarchical models.  One possibility might be to go "old school" on the analysis--code up an appropriate model, with random effects as fixed effects (as in GLM), and use that as an approximate design matrix in FMM.  Then to get at this in a random kind of way (and note it's only kind of random), use the BAYES statement. And (of course) that misses out on the repeated measures part... Steve Denham ... View more