On Fri, May 2, 2014 at 4:23 PM, Ben Bolker <bbolker@gmail.com> wrote:

> On 14-05-02 03:43 PM, Douglas Bates wrote:
> > On Fri, May 2, 2014 at 9:23 AM, Charlotte Arndt <arndtch@uni-landau.de
> > <mailto:arndtch@uni-landau.de>> wrote:
> >
> >     Dear Sir / Madam,
> >     I am analyzing some data by means of multivariate multilevel models
> >     and want to fix the residual variance on level 1 to zero. In HLM,
> >     you can do this by fixing the level 1 residual variance (sigma
> >     square) to a very small value, e.g. 0.00001. Is it possible to
> >     constrain the level 1 residual variance with lme4? It would be
> >     great, if I could use lme4 for my analyses. Thanking you in advance.
> >
> >
> > I forget how the "levels" are numbered in the multilevel modeling
> > literature but as you say "residual variance" I imagine you are
> > referring to the variance of the conditional distribution of the
> > response given the random effects.  The way the model is defined and fit
> > in the lme4 package the covariance matrix of the random effects is
> > defined relative to this variance.  In other words it would not be
> > possible to fit the model in the way you describe.
> >
> > Actually I can't imagine how such a model could make sense.  Where does
> > the variability in the conditional distribution get absorbed?
>
>
>   Actually, this can be done with blme.   See
>

But what does it mean?  What model is being fit?

>
> http://thread.gmane.org/gmane.comp.lang.r.lme4.devel/11500/
> http://thread.gmane.org/gmane.comp.lang.r.lme4.devel/11093/
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