> On Mar 22, 2018, at 1:31 PM, Michelle Kline <michelle.ann.kl...@gmail.com>
> wrote:
>
> Hi,
>
> Thanks in advance for any help on this question. I'm running multinomial
> models using the MCMCglmm package. The models have 5 outcome variables
> (each with count data), and an additional two random effects built into the
> models. The issue is that when I use the following code, the summary only
> gives me results for four of the outcome variables.
>
> Here is the code for my model:
>
> m3.random <- MCMCglmm(cbind(Opp_teacher , Dir_teacher, Enh_teacher,
> SocTol_teacher, Eval_teacher) ~ trait -1,
> random = ~ us(trait):other + us(trait):focal,
> rcov = ~ us(trait):units,
> prior = list(
> R = list(fix=1, V=0.5 * (I + J), n = 4),
> G = list(
> G1 = list(V = diag(4), n = 4),
> G2 = list(V = diag(4), n = 4))),
> burnin = burn,
> nitt = iter,
> family = "multinomial5",
> data = data,
We have no way to debug this without the data. Perhaps you should contact the
maintainer and in your message attach the data?
maintainer('MCMCglmm')
[1] "Jarrod Hadfield <j.hadfi...@ed.ac.uk>"
An equally effective approach would be to post (again with data that reproduces
the error) on the R-SIG-mixed-models mailing list since Hadfield is a regular
contributor on that list. (To me it suggests not an error since you got output
but rather a warning. Generally warnings and errors are properly labeled so you
may not have included the full output.)
--
David.
> pr=TRUE,
> pl=TRUE,
> DIC = TRUE,
> verbose = FALSE)
>
> And the summary of the main effects:
>
> post.mean l-95% CI u-95% CI eff.samp pMCMC
> traitOpp_teacher -3.828752 -4.616731 -3.067424 184.4305 5.263158e-05
> traitDir_teacher -3.400481 -4.041069 -2.813063 259.1084 5.263158e-05
> traitEnh_teacher -1.779129 -2.197415 -1.366496 624.9759 5.263158e-05
> traitSocTol_teacher -2.852684 -3.429799 -2.332909 468.7098 5.263158e-05
>
>
> It is not an issue of the suppressing the intercept, since I'm already
> doing that (see the -1 term. When I remove that term, the model solutions
> includes an intercept and only 3 additional main effects).
>
> The model does throw the following error, but after searching previous
> messages on this list, I've concluded that this error message doesn't have
> to do with my current problem. Just in case: " observations with zero
> weight not used for calculating dispersion"
>
> I have also posted a similar question on stackoverflow about a week ago,
> but with no response, so I thought I would try here. Link in case people
> want to gain reputation points for a
> response:
> https://stackoverflow.com/questions/49309027/missing-term-in-mcmcglmm-multinomial-model-results-not-in-intercept-issue
> <https://stackoverflow.com/questions/49309027/missing-term-in-mcmcglmm-multinomial-model-results-not-in-intercept-issue>
>
> And of course I've checked various other sources including the course
> notes, but can't make sense of why the 5th term is dropped from the model.
> Any help is much appreciated.
>
> Best,
>
> Michelle
>
> --
> Michelle A. Kline, PhD
>
> Assistant Professor
> Department of Psychology
> Simon Fraser University
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
David Winsemius
Alameda, CA, USA
'Any technology distinguishable from magic is insufficiently advanced.'
-Gehm's Corollary to Clarke's Third Law
______________________________________________
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
