Thanks Harold,  I will review the lmer vignette again.

On Tue, Dec 2, 2008 at 2:12 PM, Doran, Harold <HDoran@air.org> wrote:

> Richard
>
> There is much more information that you need to provide before a
> thoughtful answer can be provided. Maybe you can describe the structure
> of your data, your outcome variable, etc. There is a vignette in the
> lmer package called 'Implementation' that will show you some methods for
> model fitting.
>
> With that said, at the most basic level, a model of the form
>
> response = \mu + beta(covariate) + a_j + e_ij, a_j ~ N(0,r^2), e_ij ~
> N(0, s^2)
>
> Might be as follows in lmer
>
> > lmer(response ~ covariate + (1|covariate), ... )
>
> > -----Original Message-----
> > From: r-help-bounces@r-project.org
> > [mailto:r-help-bounces@r-project.org] On Behalf Of Richard Palmer
> > Sent: Tuesday, December 02, 2008 1:40 PM
> > To: r-help@r-project.org
> > Subject: [R] question on lmer function
> >
> > suppose something like probability(passing test) is driven by
> >
> >    1. fixed effects  -- sex
> >    2. district effects - district funding
> >    3. school effects - neighborhood income, racial
> > composition, % two parent
> >    families, ...
> >    4. class effects - teacher quality measurement,
> >    5. individual random effects - IQ.
> >
> > how would such a model be setup in lmer?  I can't find much
> > discussion on the web.
> >
> > Is there extended documentation somewhere on lmer?
> >
> > Richard Palmer
> >
> > Home       508 877-3862
> > Cell          508 982-7266
> >
> >       [[alternative HTML version deleted]]
> >
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> > PLEASE do read the posting guide
> > http://www.R-project.org/posting-guide.html
> > and provide commented, minimal, self-contained, reproducible code.
> >
>



-- 
Richard Palmer

Home       508 877-3862
Cell          508 982-7266

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