lmer() using factor() vs ordered() predictors

Hi folks,

I have some code and data posted to a gist
(https://gist.github.com/1180476) where I encounter a scenario beyond
my limited expertise. Specifically, I find that lmer() throws an error
when I attempt to fit a rather complex model, but when I attempt to
fit an analogous model after applying the ordered() function to each
of my predictors, lmer() converges fine. Thinking that maybe ordered()
dramatically changes how lmer handles the predictors, I compared the
likelihood ratios computed for both types of data for a variety of
less complex effects, and to my surprise I find that applying
ordered() to the predictors does not appear to affect subsequently
computed likelihood ratios. Does anyone have any input on these
seeming discrepant results (i.e. ordered()ness of predictors can
affect the convergence of a very complicated model but not the
likeliood ratios associated with lower-order effects)?

Cheers,

Mike

--
Mike Lawrence
Graduate Student
Department of Psychology
Dalhousie University

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~ Certainty is folly... I think. ~