[R-sig-ME] Model is nearly unidentifiable with lmer

[Ben Bolker]

Short answer: try rescaling all of your continuous variables.  It
can't hurt/will change only the interpretation.  If you get the same
log-likelihood with the rescaled variables, that indicates that the
large eigenvalue was not actually a problem in the first place.

   I don't think the standard citation from the R citation file
<https://cran.r-project.org/web/packages/lme4/citation.html>, or the
book chapter I wrote recently (chapter 13 of Fox et al, Oxford
University Press 2015 -- online supplements at
<http://ms.mcmaster.ca/~bolker/R%/misc/foxchapter/bolker_chap.html>)
cover rescaling in much detail. Schielzeth 2010
doi:10.1111/j.2041-210X.2010.00012.x gives a coherent argument about
the interpretive advantages of scaling.

   Ben Bolker


On Sun, Oct 11, 2015 at 6:37 PM, Chunyun Ma <mcypsy at gmail.com> wrote:
> Dear all,
>
> This is my first post in the mailing list.
> I have been running some model with lmer and came across this warning
> message:
>
> In checkConv(attr(opt, “derivs”), opt$par, ctrl = control$checkConv, :
> Model is nearly unidentifiable: very large eigenvalue
>
>    - Rescale variables?
>
> Here is the formula of my model (I substituted variables names with generic
> names):
>
> y ~ Intercept + Xc + Xd1 + Xd2 + Xc:Xd1 + Xc:Xd2 + Zd + Zd:Xc + Zd:Xd1 +
> Zd:Xd2 + (1 + Xc + Xd1 + Xd2 | sub)
>
> Xc: continuous var
> Xd: level-1 dummy variable(s)
> Zd: level-2 dummy variable
>
> A snapshot of data. I can also provide the full dataset if necessary.
> sub Xc Xd1 Xd2 Zd y 1 36 0 0 1 1346 1 45 0 1 1 1508 1 72 1 0 1 1246 1 12 1 0
> 1 1164 1 24 1 0 1 1295 1 36 1 0 1 1403
>
> When I reduced the # of random effect to (1+Xc|sub), the warning message
> disappeared, but the model fit became poorer.
> My question is: which variable(s) should I rescale? I’d be happy to
> better understand t
> he
>
> warning message if anyone could
> kindly
> suggest
> some
>  reference paper/book.
>
> Thank you very for your help!!
>
> Chunyun
>
>
>         [[alternative HTML version deleted]]
>
> _______________________________________________
> R-sig-mixed-models at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models