Does not the sum of probabilities (on the untransformed scale) = 1, whence
only 4 outcome categories to predict?
Cheers,
Bert
Bert Gunter
"The trouble with having an open mind is that people keep coming along and
sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
On Sat, Mar 24, 2018 at 11:15 AM, Michelle Kline <
michelle.ann.kl...@gmail.com> wrote:
> Hi David,
>
> Thanks for your comment. I haven't posted the data because they are
> unpublished and include human subjects so there are issues with sharing on
> a list serv, but I thought perhaps someone had encountered a similar
> problem and would already know the answer.
>
> I will reconsider whether my University's ethics approval would allow me to
> post the data and update the question if I think it is allowable.
>
> Michelle
>
> On Fri, Mar 23, 2018, 10:13 AM David Winsemius <dwinsem...@comcast.net>
> wrote:
>
> >
> > > 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
> >
> >
> >
> >
> >
> >
>
> [[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.
>
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