[R-sig-ME] Problem with computing gr and false convergence

[Iker Vaquero Alba]

   Thank you very much. Data is attached.

   To center and scale continuous variables, I've tried standardizing them, as 
someone suggested in some post, and I have succesfully done before. But when 
fitting the model with standardized variables, I get:

   "Error in `contrasts<-`(`*tmp*`, value = "contr.treatment") : 
  contrasts can be applied only to factors with 2 or more levels"

   Any ideas? Thank you very much!





________________________________
De: Ben Bolker <bbolker at gmail.com>
Para: r-sig-mixed-models at r-project.org
Enviado: mar,14 junio, 2011 21:09
Asunto: Re: [R-sig-ME] Problem with computing gr and false convergence

On 06/14/2011 02:57 PM, Iker Vaquero Alba wrote:
> 
> Dear R-users:
> 
> I am fitting a model with quite many terms, and I'm having a lot of
> problems. Either I get:
> 
> 
> "In mer_finalize(ans) : gr cannot be computed at initial par (65)"
> 
> or false convergence problems, when the model is a little bit
> simpler. I attach the most complex one with "verbose=TRUE" to see if
> you can help me detectt where the problem is:
> 
> 
>hatchcoltailmodel1<-lmer(nhatch~sex+mod+briventral+brithr+tlength+cond+briventral:brithr+briventral:tlength+briventral:cond+briventral:sex+briventral:mod+
>+
>brithr:tlength+brithr:cond+brithr:sex+brithr:mod+tlength:cond+tlength:sex+tlength:mod+
>
>
cond:sex+cond:mod+(1|site/pair)+(1|year),family=poisson,na.action=na.omit,verbose=TRUE)

>
>  0:           nan:  1.06217 0.584705 0.261488 -15.3440 -0.757161
> 16.9953 3.85760  1.53215  1.30924  5.14768 -0.0259057 0.0675839
> 0.172804  9.56398 0.000488889 -0.000119170 0.0156963 0.00445958
> -0.109915 -0.0119783 -0.0113610 -0.00132653 0.00594852 -2.29204e-05
> -0.0678690 0.00288760 0.321050 -0.0107392 0.0195566 -0.00242138
> -0.0538382 -0.0866086 -0.00632440 -0.168793 -0.0123981 0.00379237
> -0.00313671 -0.0228579 0.504940      nan -0.722186 -1.31712 -0.618912
>  -1.25492 Mensajes de aviso perdidos In mer_finalize(ans) : gr cannot
> be computed at initial par (65)
> 
>

  Very  hard to say without a reproducible example.  Can you post the
data somewhere?

  How big is your data set?

  If any of your variables are continuous, consider centering and
scaling them (e.g. using scale())


  Other than that, I only have a couple of coding style suggestions.

1. I *think* but am not sure that your very long model above is
equivalent to

(briventral+brithr+tlength+cond+sex+mod)^2-mod:sex

(all main effects + all pairwise interactions except mod:sex) but you
should of course check that (and the order might not be the same as the
model you have above).

2.  It is best to use the 'data' argument to specify a data frame
(rather than attach()ing or having the variables floating around in the
workspace)

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