[R-sig-ME] ordinal regression with MCMCglmm

[Jarrod Hadfield]

Hi Kari,

The simplest model is


m1<-MCMCglmm(resp~treat, random=~group, family="ordinal",  
data=your.data, prior=prior)

as with multinomial data with a single realisation, the residual  
variance cannot be estimated from the data. The best option is to fix  
it at some value. most programs fix it at zero but MCMCglmm will fail  
to mix if this is done, so I usually fix it at 1:


prior=list(R=list(V=1, fix=1), G=list(G1=list(V=1, nu=0)))

I have left the default prior for the fixed effects (not explicitly  
specified above), and the default prior random effect variance  
structure (G) which has a zero degree of belief parameter. Often this  
requires some/more thought, especially if there are few groups or  
replication within groups is low. Sections 1.2, 1.5 & 8.2 in the  
CourseNotes cover priors for variances.


Currently there is no option for specifying priors on the cut-points -  
the prior is flat and improper. The posterior in virtually all cases  
will be proper though.

Cheers,

Jarrod

Quoting Kari Ruohonen <kari.ruohonen at utu.fi>:

> Hi,
> I am trying to figure out how to fit an ordinal regression model with
> MCMCglmm. The "MCMCglmm Course notes" has a section on multinomial
> models but no example of ordinal models. Suppose I have the following
> data
>
>  > data
>    resp treat group
> 1     4     A    1
> 2     4     A    1
> 3     3     A    2
> 4     4     A    2
> 5     2     A    3
> 6     4     A    3
> 7     2     A    4
> 8     2     A    4
> 9     3     A    5
> 10    2     A    5
> 11    1     B    6
> 12    1     B    6
> 13    1     B    7
> 14    2     B    7
> 15    2     B    8
> 16    3     B    8
> 17    2     B    9
> 18    1     B    9
> 19    2     B   10
> 20    2     B   10
>
> and the "resp" is an ordinal response, "treat" is a treatment and
> "group" is membership to a group. Assume I would like to fit an ordinal
> model between "resp" and "treat" by having "group" effects as random
> effects. How would I specify such a model in MCMCglmm? And how would I
> specify the prior distributions?
>
> All help is greatly appreciated.
>
> regards, Kari
>
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>



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