Am 12.09.2014 um 17:55 schrieb "Emmanuel Curis" <emmanuel.curis at parisdescartes.fr>:
Double check your results, you will see that there is agreement also
for random effects: the column to use is Std. Dev. which is indeed in
the confidence intervals given by confint --- just like standard
deviation for the residuals.
It just happen that confidence intervals are so wide, that they also
include the Variance value, but thats ? bad luck ?.
On Fri, Sep 12, 2014 at 02:52:11PM +0000, lorenz.gygax at agroscope.admin.ch wrote:
? Dear Martin,
?
? Many thanks for this explanation which, of course, is very reasonable ;-)
?
? But - and I may be real slow on this - why is the same seemingly not true for the random effects as well (summary and confint give the same absolute values)?
?
? Cheers, Lorenz
? >> If I do the summary () this is what I get for the random effects part of the output.
? >
? >> Random effects:
? >> Groups Name Variance Std.Dev.
? >> val:(part:ID) (Intercept) 0.4599 0.6782
? >> part:ID (Intercept) 0.1773 0.4211
? >> ID (Intercept) 0.1278 0.3575
? >> Residual 9.4302 3.0709
? >> Number of obs: 1833, groups: val:(part:ID), 214; part:ID, 72; ID, 25:
? >
? >
? >> If I do
? >
? >> confint (HHbT.fin.lmer, method= 'profile')
? >
? >> I get
? >
? >> 2.5 % 97.5 %
? >> .sig01 0.41713241 0.9210729
? >> .sig02 0.00000000 0.7535615
? >> .sig03 0.00000000 0.6697109
? >> .sigma 2.96898087 3.1786606
? >
? >> Where the above listed variances for the random effects fit nicely into the confidence intervals (.sig0x) but not the value for the residuals / .sigma where the variance from the summary seems to be approximately squared in respect to the confidence interval.
--
Emmanuel CURIS
emmanuel.curis at parisdescartes.fr
Page WWW: http://emmanuel.curis.online.fr/index.html