[R] lme() with known level-one variances

[J.R. Lockwood]

> 
> >
> > If I understand your request correctly, you want to use something like
> > "weights=varIdent(...)" as an argument to lme().  varIdent and the other
> > varFunc constructors have an argument "fixed" that allow you to specify
> > values for some or all of the coefficients of the variance function.
> > See ?varIdent.  The actual error variance will be varFunc() * sigma^2,
> > where sigma^2 is estimated.
> >
> 
> That's the problem.
> 
> As happens in meta-analysis as well, the problem is to estimate a model
> with a variance component fixed. Not fixed up to a scale parameter. Fixed.
> 
> In meta-analysis the model is that within each trial a treatment effect
> parameter is constant, and as the trial is large the variance of the
> estimated treatment effect is very accurately known conditional on the
> true treatment effect for that trial. The unconditional variance is then
> the known conditional variance plus an unknown variance.
> 
> It doesn't seem that lme() is designed for this, and last time I tried to
> do it I gave up and changed the model more or less as you suggest.

Thanks to you both for your helpful input.  Thomas is correct that I
want to treat them as fixed (no free parameters) rather than fixed up
to a scale factor.  Indeed I have not yet been able to keep lme() from
estimating two variance components.  If Thomas gave up, that's pretty
much enough evidence for me that I need to look elsewhere.

I do not think that for this particular problem, writing a routine to
do the REML/ML estimation of the inter-study variance component would
be too difficult.  I will add this to the growing list of items I
would like to contribute to this great project.

Thanks again and best regards,

J.R. Lockwood
412-683-2300 x4941
lockwood at rand.org
http://www.rand.org/methodology/stat/members/lockwood/

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