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

[Chunyun Ma]

​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
​

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