[R-sig-ME] Variance component models using lmer
Luciano La Sala
lucianolasala at yahoo.com.ar
Mon Jan 3 20:40:10 CET 2011
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
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