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interpretation of predict plot (glmer)

As you can see, these kinds of e-mails to me personally often slip
through the cracks.  It's quite a bit better to send them to
r-sig-mixed-models at r-project.org, where someone else might answer them,
and where the answers
On 14-01-16 09:42 AM, Barbara horta e costa wrote:
Well, I don't know; it seems reasonable, except that (1) you might
want to have values of your continuous predictor repeated for all the
factor combinations and (2) 1000 values of your continuous predictor
might be overkill.  I like to use expand.grid for this, e.g.

newdat2 <- with(dataCovosOctopus,
  expand.grid(CovosTotalInOut_amostrados=seq(10, 1000, length.out=101),
              Season3=levels(Season3),
              VesselCode=levels(VesselCode)))
Don't quite know what to say about this.  It looks like there are a
bunch of overlapping values along the lower curve,  so perhaps you have
two 'outlier' random effects?  Don't know why one can't easily see the
response.  I often use ggplot to add distinctions among random effect
levels and fixed effects.
Again hard to say.