[R] lmer (multinomial response variable ~ fixed + (1|random), family='"multinomial" ???)
bbolker at gmail.com
Fri May 31 02:38:38 CEST 2013
Maggie Wisniewska <maggie.wisniewska <at> gmail.com> writes:
> I am trying to run glmm to test the effect of the three fixed effects [AGE
> (weaned vs. unweaned claf), LOCATION (zoo vs. park), MOTher's social status
> (matriarch vs. nonmatriarch)] and one random effect [ID (12 different
> calves of whom I have multiple but unbalanced observations)] on the a
> multinomial response variable [DIST (distance from mom at less than 2
> meters,between 2-5 meters and at more than 5 meters). Is the *family =
> binomial* argument in my code incorrect for my data? If it is incorrect,
> is there a way to test this model with *multinomial response variable*?
> = "logit")
This would probably be better asked on the specialized
r-sig-mixed-models at r-project.org mailing list.
It looks like you really want to fit an ordinal model
(i.e. your categories are naturally ordered, as opposed to
a case where your responses were unordered, e.g.
"chocolate", "strawberry", "vanilla", "maple walnut").
The 'ordinal' package will allow you to fit these kinds
PS (somewhat tangential)
As far as I know the only mixed model package available for R that can
handle multinomial models in a simple way is the MCMCglmm package.
Multinomial models are relatively easy to code as variations on binomial
(the latter is provided by the INLA web site, another mixed model package)
but this won't help if you just want a quick "black-box" solution.
More information about the R-help