[R-sig-ME] Multivariate mixed models with different outcome distributions

[Ben Bolker]

   I didn't realize that brms does multi-type models, but apparently it 
does:

https://cran.r-project.org/web/packages/brms/vignettes/brms_multivariate.html

   ... so yes, I would go for brms in this case.

   cheers
    Ben


On 2022-12-14 12:09 p.m., Timothy MacKenzie wrote:
> Dear Ben,
> 
> Thank you for the hint. Regarding MCMCglmm, I couldn't find "beta" in
> the family of allowable distributions in the package. Did you have a
> specific set of distribution families in mind to handle normal and
> beta responses simultaneously?
> 
> Also, I noticed the brms package apparently can handle different
> response distributions, is there a reason, in your expert opinion, to
> opt for MCMCglmm?
> 
> Many thanks,
> Tim M
> 
> On Tue, Dec 13, 2022 at 9:28 PM Ben Bolker <bbolker using gmail.com> wrote:
>>
>> MCMCglmm can handle this case
>>
>> On Tue, Dec 13, 2022, 10:14 PM Timothy MacKenzie <fswfswt using gmail.com> wrote:
>>>
>>> Hello Colleagues,
>>>
>>> I have a multivariate data structure (below) where the dependent
>>> variables (DV) seem to have different distributions.
>>>
>>> For instance, *ac* is measured in proportions and perhaps
>>> beta-distributed, but *fl* and *le* may be normally distributed.
>>>
>>> Would it make methodological sense to fit such DVs in a multivariate
>>> mixed model given that they are theoretically related but practically
>>> measured on different scales?
>>>
>>> Any resources to provide mixed model strategies in such a situation?
>>>
>>> Many thanks for your help,
>>> Tim M
>>>
>>> Score ~ DV + (1 | subj_id) ## Would this make sense?
>>>
>>> # Data structure:
>>> subj_id  DV     Score
>>> 1            ac      .5
>>> 1            fl        23.1
>>> 1            le       1.4
>>> 2            ac      .7
>>> 2            fl        19.6
>>> 2            le       2.1
>>>
>>> _______________________________________________
>>> R-sig-mixed-models using r-project.org mailing list
>>> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models

-- 
Dr. Benjamin Bolker
Professor, Mathematics & Statistics and Biology, McMaster University
Director, School of Computational Science and Engineering
(Acting) Graduate chair, Mathematics & Statistics
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