[R] MCMCglmm multinomial model results

[David Winsemius]

> On Mar 22, 2018, at 1:31 PM, Michelle Kline <michelle.ann.kline at 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.hadfield at 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]]
> 
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David Winsemius
Alameda, CA, USA

'Any technology distinguishable from magic is insufficiently advanced.'   -Gehm's Corollary to Clarke's Third Law