Testing the proportional odds assumption in runmlwin

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Eagg1986
Posts: 14
Joined: Fri Apr 05, 2013 3:24 pm

Testing the proportional odds assumption in runmlwin

Post by Eagg1986 »

Hi there,
I am running some multilevel ordinal regression models and am not sure how to test the proportional odds assumption. In single level modelling the brant command performs this test but I have been unsuccessful using this command in conjunction with runmlwin.
Any help would be gratefully received.
Many thanks,
Beth
GeorgeLeckie
Site Admin
Posts: 432
Joined: Fri Apr 01, 2011 2:14 pm

Re: Testing the proportional odds assumption in runmlwin

Post by GeorgeLeckie »

Hi Beth,

The brant test is not implemented in MLwiN and therefore is not available in MLwiN.

Presumably the brant test simply tests the equality of the parameters across the various log-odds contrasts which you could make.

So you could fit a model where you relax (at least partially) the proportional odds assumption and then use Wald tests to test the equality of the parameters across the contrasts.

Alternatively, if you fit the models by MCMC you could fit two models and compare their DIC statistics. The first model would be the ordinal model where you impose the proportional odds assumption, the second model would be the same model, but where you relax the proportional odds assumption

Take a look at the LEMMA online course which has a module (Module 9) on multilevel ordinal models.

http://www.cmm.bris.ac.uk/lemma/login/index.php

Best wishes

George
Eagg1986
Posts: 14
Joined: Fri Apr 05, 2013 3:24 pm

Re: Testing the proportional odds assumption in runmlwin

Post by Eagg1986 »

Hi George,
Thanks for your suggestions, they are very helpful and I'll give them a try. Just to clarify, a model using the proportional odds assumption would look like this (to use the example given):

quietly runmlwin use4 cons (age lc1 lc2 lc3plus urban, contrast(1/3)), ///
level2(district: (cons, contrast(1/3))) ///
level1(woman:) ///
discrete(dist(multinomial) link(ologit) denom(cons) basecategory(4)) ///
nopause

While a model not making the assumption would be specified as follows:
quietly runmlwin use4 age lc1 lc2 lc3plus urban cons, ///
level2(district: cons) ///
level1(woman) ///
discrete(dist(multinomial) link(ologit) denom(cons) basecategory(4)) ///
nopause

The difference being that the command 'contrast (1/3)' in the first model states that a single coefficient will be estimated for all contrasts, implying proportional odds? I just want to check I am understanding you correctly.

Many thanks,
Beth
GeorgeLeckie
Site Admin
Posts: 432
Joined: Fri Apr 01, 2011 2:14 pm

Re: Testing the proportional odds assumption in runmlwin

Post by GeorgeLeckie »

Hi Beth,

Yes that's correct.

In the first model only the intercept varies across the log-odds contrasts

In the second model all parameters vary across the log-odds contrasts

It would be worth using runmlwin to replicate this test which is illustrated in the lemma online course I referred to in an earlier post in this thread.

Best wishes

George
Eagg1986
Posts: 14
Joined: Fri Apr 05, 2013 3:24 pm

Re: Testing the proportional odds assumption in runmlwin

Post by Eagg1986 »

Thank you George, that's much appreciated.
Many thanks,
Beth
SabineKatzdobler
Posts: 18
Joined: Sat Sep 05, 2020 10:22 am

Re: Testing the proportional odds assumption in runmlwin

Post by SabineKatzdobler »

Good day Goerge,

after I saw the discussion about the proportional odds assumption, I would like to ask the following question:

Can you provide me an example for the "runmlwin" syntax for running a within between random effects model (REWB) with an ordinal dependent variable (involving 10 categories)? Additionally, the proportional odds assumption cannot be fulfilled and I have six independent variables (continuous and categorical) as well as two levels.

Kind regards,

Sabine
stepanyanmir
Posts: 1
Joined: Tue Mar 09, 2021 11:28 am

Re: Testing the proportional odds assumption in runmlwin

Post by stepanyanmir »

Much appreciated
Thank you Goerge, i saw your name in every second thread and you are answering very well
hope we will learn from you
Best Wishes
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