[R-sig-ME] Multilevel Ordinal Logistic Regression: clmm warnings

[David Duffy]

On Sat, 23 Jun 2012, Nicholas Sabin wrote:

> I am working with repeated measures for subjects and the dependent variable
> is ordered categories.  So I am working on building a Multilevel Ordinal
> Logistic Regression model.
>
> Example Data:
>
> ID      Cycle     X          X2    PerfCat
> 100         1     3.5        12    1
> 100         2     7.6        57    4
> 100         3     6.6        43    3
>
> Model.mlol <- clmm(as.ordered(PerfCat) ~
>       X+X2+(1|ID),
>       data=ExampleData)
>
> "In update.uC(rho) : Non finite negative log-likelihood
>  at iteration 165"

I presume Rune Haubo Christensen will give a better answer but this
doesn't sound very good.  What did

clmm(as.ordered(PerfCat) ~ X + (1|ID)..

and

clmm(as.ordered(PerfCat) ~ poly(X,2) + (1|ID)..

give?

Also, the rule of thumb is that ordinal variables with five or more levels 
can usually be treated as continuous without inference problems.  That is, 
you should be getting answers close to your LMM result.

Cheers, David Duffy.