[R-sig-ME] Covariance Matrix of fixed effects in lmer()

[Matthias Suter]

Is there a straight forward way, to get the scaled covariance matrix from a 
lmer()? 

E.g.
lmerout <- lmer(y ~ x1 + x2 + x3  + (1 | Groupingfactor), data)

summary(lmerout) gives the "Correlation of Fixed Effects"; I would like to 
have direct access to the covariance matrix.

As analogy in lm():

lmout <- lm(y ~ x1 + x2 + x3, data)

Here, the scaled covariance matrix is:

summary(lmout)$sigma^2 * summary(lmout)$cov.uns

Thanks for any helpful answer,
Matthias