Dear list members

Is there a direct access to the covariance matrix of fixed effects in lmer(). For example, with ...


summary( lmer(y ~ x1 + x2 + x3  + (1 | Groupingfactor), data) )

... we receive the    "Correlation of Fixed Effects"


Is there a straight forward way to get the covariance matrix to which the correlation matrix refers?



The analogue in a lm() would be:

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

To get the covariance matrix, we have e.g.:

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


With many thanks in advance,
Matthias

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Matthias Suter, Dr.
Forage and Grassland
Forschungsanstalt Agroscope Reckenholz-Tänikon ART
Reckenholzstrasse 191, CH-8046 Zürich

Tel. +41 44 377 75 90
Fax +41 44 377 72 01
matthias.suter@art.admin.ch
www.agroscope.ch
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