zero random effect sizes with binomial lmer

Daniel Ezra Johnson <johnson4 <at> babel.ling.upenn.edu> writes:
...

More broadly, is it hopeless to analyze this data in this manner, or  
else, what should I try doing differently? It would be very useful to  
be able to have reliable estimates of random effect sizes, even when  
they are rather small.

...

You might try with mcmcsamp to get a better view of posterior distributions of
your parameters. It might be the case that MLE for item variance is near 0, while
its posterior distribution covers also values that are higher than 0.

Gregor