[R-sig-ME] Help! What are the typical diagnosis that one can do when facing "fail to converge"?

[Ben Bolker]

arun <smartpink111 at ...> writes:

> I also had a similar warning message but with lmer ( (Warning
> message:In mer_finalize(ans) : false convergence (8)).  I used
> verbose=TRUE in the model statement.  It will print each iteration
> estimates.  I also tried to increase the iterations, but it didn't
> work.  Then, I found this blog
> (http://davidhughjones.blogspot.com/2009/11/lme-false-convergence.html).
> It says to look for betas with estimates very low and divide that
> variable by 10 or 100.  This was the only solution that worked for
> me.  But, the estimates of beta for the variable and its
> interactions will be 10 fold higher than expected.

  A more generic piece of advice would be to scale and center
all continuous predictor variables ... it won't always
help, but it's easy to try.

orig_data <- data.frame(V1=factor(1:5),V2=1:5,V3=(1:5)*0.001,V4=LETTERS[1:5])
scaled_data <- as.data.frame(lapply(orig_data,
                   function(x) {
                        if (class(x) %in% c("integer","numeric")) {
                              scale(x) } else x
                    }))

In doing this, the scaling and centering factors seem to get lost,
so it's not a perfect solution.
A full-fledged auto-scaling solution *might* be built into some
future version of lme4 ...