Multilevel Ordinal Logistic Regression: clmm warnings
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.