[R] what does this warnings mean? and what should I do?

[Berton Gunter]

 Spencer:

(warning: highly biased, personal opinions)

My $.02
> 	  Looking now at your output, I notice that "Corr" between
> "(Intercept)" and "trust.cz1" for the "Random Effects" "commid" is
> 1.000.  This says that the structure of your data are not adequate to
> allow you to distinguish between random effects for "(Intercept)" and
> "trust.cz1" for "commid", while simultaneously estimating all 
> the fixed
> effects you have in the model.

Quite right. Design is the cause; overfitting/identifiability is the
symptom.
> 
> 	  If I were you, I'd start be deleting all the terms 
> from the model
> that don't have a "Signif. code" beside it in the table of "Fixed
> effects" and then refit the smaller model, preferably also using
> 'method="AGQ"'.  

Well, this might work, but it's also a prescription for overfitting a highly
biased model.

What he really needs to do is carefully rethink. What is a parsimonious
model given the data at hand? Unfortunately, this is far from a trivial
issue. Model choice for nonlinear model fitting is conceptually and
statistically difficult.

IMHO, the tendency to overfit mechanistically motivated models with
insufficient, poorly designed data is a ubiquitous scientific practice,
rarely understood by scientists (due to the complexity). As a result, there
are a lot of questionable results published in peer-reviewed literature.
Eventually it gets sorted out, but it can take a while. See Kuhn and
Feyerabend, for example.

Always enjoy your comments. Keep 'em coming.

-- Bert