[R-sig-ME] warnings ranef and design of a binomial model

[Robert ESPESSER]

Dear R users,

I have a question about model design.
One group of 20 subjects run the A experiment, with 17 binary responses by subject.
An other group of 20 subjects run the 2 experiments B and C, with 20 binary responses by subject, 
for both of the 2 experiment.

I want to study the effect of the  factor "expe"  
I tried this covariance model:
mod.glmer <-  glmer( vd ~ dlms*expe +(1|subject) +(0+dlms|subject) , 
              family=binomial, ....)

where:
dlms is a numeric factor (-2,-1,0, 1,2)
expe is a 3 levels factor , coding the experiment (A or B or C)

vd is the success/fail matrix.

The model with a random slope is clearly better than an intercept-only model.

the results look plausible, ranef(mod.glmer, postVar=T) was OK for the
Intercept, but failed
to compute the postvar of the random slope , with these warnings:
1: In min(x): no argument found for min; Inf is returned
It's the same for max.

I'm  suspecting  that my model is perhaps badly designed , concerning the 
unbalanced repartition of the subjects across the experiments. Is it correct ?

Thanks for any comments or suggestions.

####
sessionInfo()  is:
R version 2.7.2

lme4_0.999375-26
Matrix_0.999375-13


Robert Espesser
Laboratoire Parole et Langage  UMR 6057, CNRS
29 Av. Robert Schuman  13621 AIX    (FRANCE)
Tel: +33 (0)4 42 95 36 26   Fax: +33 (0)4 42 95 37 88
http://www.lpl-aix.fr