[R-sig-ME] Variance component models using lmer

[Luciano La Sala]

Dear everyone, 

I have a dataset consisting of 144 measurements of egg volume from 48 nests
(3 eggs/nest). I am interested in answering the question of how much of the
variation in the response variable (egg volume) can be attributed to
within-nest variation and how much to among-nests variation. My model was
specified as follows: 

> model <- lmer(EggLength ~ NestID + (1|NestID), data = Data)
> summary(model)

Linear mixed model fit by REML 
Formula: EggLength ~ NestID + (1 | NestID) 
   Data: Data 
   AIC   BIC logLik deviance REMLdev
 712.4 724.3 -352.2    697.9   704.4

Random effects:
 Groups   Name        Variance Std.Dev.
 NestID   (Intercept) 5.5917   2.3647  
 Residual             4.5025   2.1219  

Number of obs: 144, groups: NestID, 48

Fixed effects:
            Estimate Std. Error t value
(Intercept) 68.02159    1.26104   53.94
NestID       0.02753    0.01540    1.79

Correlation of Fixed Effects:
       (Intr)
NestID -0.952

>From the above output I extracted the variance components by squaring the
standard deviations, then expressing them as percentages: 

> vars <- c(5.5917, 4.5025)
> 100*vars/sum(vars)
[1] 55.39518 44.60482

At this point, I would conclude that egg volume varied 55.4% among clutches
and 44.6% within clutches. 

I'd appreciate suggestions/corrections to my model specification and results
interpretation. 

Thank you in advance.

Luciano