[R-sig-ME] variance-covariance matrix of the estimations of the variance-covariance matrix of the random effects
bates at stat.wisc.edu
Fri Jan 14 16:04:34 CET 2011
Variances and covariances of estimators of variance components are
usually of little value because the distribution of the estimators are
often highly skewed. See the notes at
for illustration of such cases. Notice Figure 4 in particular.
In theory you could evaluate the information matrix for the profiled
deviance and use the "delta method" to determine an information matrix
for the variance-covariance parameters but it would take considerable
effort and probably not produce useful information.
On Thu, Jan 13, 2011 at 3:51 PM, Resche Rigon Matthieu
<matthieu.resche-rigon at paris7.jussieu.fr> wrote:
> Dear all,
> I try to obtain the variance-covariance matrix of the estimations of the
> variance covariance matrix of the random effects. I know how obtain it using
> lme but I would like to obtain it with lmer(). Is it possible?
> Moreover do you know which formula is applied by ranef() to extract the
> conditional modes and the conditional variance-covariance
> matrix of the random effects?
> Thanks in advance
> R-sig-mixed-models at r-project.org mailing list
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