**From:** Joerg Schaber (*Joerg.Schaber@uv.es*)

**Date:** Fri 14 Nov 2003 - 02:49:34 EST

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Message-id: <3FB3A80E.1040909@uv.es>

I naively thought when I can give estimates of the random effects I

should also be able to calculate confidence levels of these estimates

(that's what statistics is about, isn't it?)

For example, similar to the fixed case, I can calculate a

variance-covariance matrix (C) for the random effects (e.g. following

Hemmerle and Hartley,TECHNOMETRICS 15 (4): 819-831 1973) and using the

t-value for the given confidence level and degrees of freedom (t), I can

estimate confidence intervals for random effect i (r[i]) as something

like r[i] +- t*sqrt(C[i][i]).

What does the statistician say?

Douglas Bates wrote:

*>Joerg Schaber <Joerg.Schaber@uv.es> writes:
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*>
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*>
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*>
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*>>I have a linear mixed-effects model object and want to extract the 95%
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*>>confidence intervals for the fixed and random effects, respectively. I
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*>>found the function intervals() for confidence intervals for the fixed
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*>>effects but no corresponding function for the random effects. Does it
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*>>exist or do I have to calculate the confidence intervals for the
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*>>random effects myself?
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*>>
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*>>
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*>
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*>You have to calculate them yourself, partly because it is not clear
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*>what such an interval should be. Technically, the random effects are
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*>not parameters and defining a "confidence interval" on a random
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*>variable that is part of the model is, at the very least, awkward.
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*>
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*>
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-- ---------------------------------------------------------- Jörg Schaber Instituto Cavanilles de Biodiversidad y Biologia Evolutiva Universidad de Valencia Tel.: ++34 96 354 3666 A.C. 22085 Fax.: ++34 96 354 3670 46071 Valencia, España email : jos@uv.es______________________________________________ R-help@stat.math.ethz.ch mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help

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