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

[Ben Bolker]

  The link to the chapter supplement should be

<http://ms.mcmaster.ca/~bolker/R/misc/foxchapter/bolker_chap.html>

  sorry about that
    Ben Bolker


On 15-10-11 08:27 PM, Porco, Travis wrote:
> Sorry to bother you; the hyper link to your chapter supplements is
> giving Bad Request/ error 400. --tcp 
> ________________________________________ From: R-sig-mixed-models
> [r-sig-mixed-models-bounces at r-project.org] on behalf of Ben Bolker
> [bbolker at gmail.com] Sent: Sunday, October 11, 2015 5:18 PM To:
> Chunyun Ma Cc: r-sig-mixed-models at r-project.org Subject: Re:
> [R-sig-ME] Model is nearly unidentifiable with lmer
> 
> 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]]
>> 
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