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

[J.R. Lockwood]

Dear Vito,

Thank you for your response.  I still have some concerns:

>
> See the rmeta package on CRAN (the metaDSL() function would do what you are
> looking for).

It is not clear to me that this function does what I need.  I
apologize for casting my original question in terms of a
meta-analysis; it is a bit of a red herring.  My more general question
is whether it is possible to tell lme() to treat some variance
components as known, and to estimate others conditional on them.

> 
> BTW, in your code note:
> 
> i)In the model estimation, the estimated coefficients beta have to be
> weighed by the inverse of their variance (the smaller the variance, the more
> accurate the estimated beta, the more important its influence on the pooled
> estimate)

Unless I am misinterpreting, the "weights" argument that I passed to
lme() is inverted.  But after further consideration I do not think
that weighting is what I am seeking.

> ii) As far as I know, it makes no sense to set no.group=no.observations;
> otherwise you could not estimate the intra-group variance.
> 

I am not sure to what function the arguments you reference belong
(they do not appear to be part of meta.DSL()).  But the larger point
is that I do not want to estimate the intra-group variances -- I want
to treat them as known.

best,

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

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