st: Re: question about mixed-effects ordinal regression in STATA 13

[Darcy Hannibal <dlhannibal@ucdavis.edu>]

Although I did not receive response to this form the statlist, I have 
had several people contact me who have the same question and want to 
know if I received a response or found out anything more.  I am writing 
this email to post for the record my response to the latest inquiry so 
that it might be helpful or expanded on by anyone familiar with mixed 
ordinal regression. Please see below:

"No one responded, but after doing quite a bit more reading it is clear 
that meologit and meglm use an algorithm that does assume proportional 
odds. Unfortunately STATA does not provide a way to test the 
proportional model with a mixed model.  Non-proportional odds separate 
out the coefficients of the predictors by each category of the ordinal 
outcome and you can force STATA to do this by recoding your outcome 
variable into multiple separate binary outcomes for your cutpoints.

There is a program called SuperMix that will do it and allows you to do 
proportional odds models, non-proportional odds models, or 
partial-proportional odds models. It is not very user friendly and you 
will have to read an extensive amount of documentation to use it. I 
ended up using that to assess the variables in my models for the 
proportional-odds assumption and then ran the final model in STATA to 
produce predicted probabilities and make graphs. Fortunately, all of the 
variables in my final model met the assumption. You can get estimates 
out of SuperMix, but it is pretty time consuming.

There is a free version of SuperMix you can download from their website 
at: http://www.ssicentral.com/supermix/downloads.html. [additional note: 
the non-free version is super expensive at $425 but so super useful I 
would buy it at a more affordable price of say $100-$200; unless, of 
course, STATA 14 makes it possible to do everything SuperMix can do].

Although the website states it limits the size of the model you can 
analyze, I did not have any problems and had a data set much larger than 
what is supposed to be allowed in the student version. Although they 
state they do not provide support for the student version, they were 
willing to respond to the few questions I asked, but that was after I 
read much of the documentation and had figured most of it out. So, I 
think they are willing to help those who've already done as much as 
possible on their own and are just a little bit stuck."

I hope that helps,
Darcy


On 12/5/2013 1:15 PM, Darcy Hannibal wrote:
> Hello,
>
> I have a question about the assumptions for the models using either 
> the meologit or meglm (ordinal family) commands. None of the 
> documentation I have found for these new commands available in version 
> 13 mention anything about testing for whether the data meet the 
> proportional odds assumption. Since there are different varieties of 
> ordinal models and not all of them are constrained by proportional 
> odds I am wondering if the models used in these two commands do not 
> assume proportional odds. The brant command will test proportional 
> odds, but it only works after the ologit command.
>
> Can anyone tell me if the proportional odds assumption applies to 
> meologit and meglm (ordinal family). If so, is there a simple way to 
> test for this in STATA or does it have to be done by hand?
>
> Thank you in advance for any advice you can give.
> --Darcy

--
Darcy L. Hannibal, PhD
Staff Research Associate III Supervisor

McCowan Animal Behavior Laboratory for Welfare and Conservation
Department of Population Health and Reproduction

Behavior Management
Brain, Mind, and Behavior Unit
California National Primate Research Center

University of California at Davis

Office: 3029-B CNPRC
Phone: 530-752-1586

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