[R] conf int mixed effects

[Harold Doran]

I am very curious about this. If a particular growth model is specified to reflect repeated observations on individual i in unit j, such as:

y_{tij} = [B_{00} + B_{01}*(TIME)]+[u_{00}+u_{01}*(TIME)+ e_{tij}]

where Bs are the fixed effects and the u's are the random effects.

The growth of individual i is then computed as:

B_{01} + u_{01}

Is it appropriate to compute a confidence interval around this growth rate? I so, how might this be accomplished? Based on Doug's comments below, it would seem that only a CI can be formulated for the fixed portion of the model.

I would appreciate any clarification.

HCD


------
Harold C. Doran
Director of Research and Evaluation
New American Schools
675 N. Washington Street, Suite 220
Alexandria, Virginia 22314
703.647.1628
 
 
 


-----Original Message-----
From: Douglas Bates [mailto:bates at stat.wisc.edu]
Sent: Thursday, November 13, 2003 10:11 AM
To: Joerg Schaber
Cc: r-help at stat.math.ethz.ch
Subject: Re: [R] conf int mixed effects


Joerg Schaber <Joerg.Schaber at uv.es> writes:

> I have a linear mixed-effects model object and want to extract the 95%
> confidence intervals for the fixed and random effects, respectively. I
> found the function intervals() for confidence intervals for the fixed
> effects but no corresponding function for the random effects. Does it
> exist or do I have to calculate the confidence intervals for the
> random effects myself?

You have to calculate them yourself, partly because it is not clear
what such an interval should be.  Technically, the random effects are
not parameters and defining a "confidence interval" on a random
variable that is part of the model is, at the very least, awkward.

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