Covariance Matrix of fixed effects in lmer()

Matthias Suter <matthias.suter at ...> writes:

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

It sounds like you want vcov() ... ?  (vcov() works for
lm() results, and many other model types, too ...

  methods(class="mer")
  showMethods(class="mer") ## S4 methods

## or if using development lme4 from r-forge:
  methods(class="merMod")


e.g.

(fm1 <- lmer(Reaction ~ Days + (Days|Subject), sleepstudy))
vcov(fm1)

2 x 2 Matrix of class "dpoMatrix"
            (Intercept)      Days
(Intercept)   46.574978 -1.451084
Days          -1.451084  2.389469

  cheers
   Ben Bolker