[R-sig-ME] Large variance and SD for random effects

[cumuluss]

Hello,
the result of my GLMM with binomial error structure revealed for one of
the random intercepts and slopes variances and Sd's larger then 1

> Generalized linear mixed model fit by maximum likelihood (Laplace Approximation) ['glmerMod']
>  Family: binomial  ( logit )
> Formula: obs.yn ~ z.lengthxyz + z.obsX + Spe_tr_subspecie + (1 | commu) +  
>     (1 + z.lengthxyz + z.obsX | Siteun) + (1 + z.lengthxyz +  
>     z.obsX + Spe_tr_subspecie_a.c + Spe_tr_subspecie_b.c +  
>     Spe_tr_subspecie_c.c | behavior)

> Random effects:
>  Groups   Name                  Variance Std.Dev. Corr                         
>  commu    (Intercept)           0.614004 0.78358                               
>  Siteun   (Intercept)           0.521198 0.72194                               
>           z.lengthxyz           0.001016 0.03188   1.00                        
>           z.obsX                0.306931 0.55401  -0.17 -0.19                  
>  behavior (Intercept)           2.966139 1.72225                               
>           z.lengthxyz           0.030171 0.17370   0.77                        
>           z.obsX                0.412169 0.64200   0.20 -0.36                  
>           Spe_tr_subspecie_a.c  1.853903 1.36158   0.58  0.62  0.11            
>           Spe_tr_subspecie_b.c  3.973439 1.99335   0.51  0.23  0.25  0.65      
>           Spe_tr_subspecie_c.c  7.401343 2.72054   0.39  0.30  0.47  0.79  0.60
> Number of obs: 4413, groups:  commu, 144; Siteun, 108; behavior, 31

Now I wonder, whether that is a reason to worry, that the result could
be not valid?
Thanks in advance for any comments!
Paul