Message-ID: <5a165e4f050527064829819768@mail.gmail.com>
Date: 2005-05-27T13:48:38Z
From: Koen Pelleriaux
Subject: longitudinal survey data
In-Reply-To: <Pine.A41.4.61b.0505261305140.303294@homer12.u.washington.edu>
On 5/26/05, Thomas Lumley <tlumley at u.washington.edu> wrote:
> If you *want* to fit mixed models (eg because you are interested in
> estimating variance components, or perhaps to gain efficiency) then it's
> quite a bit trickier. You can't just use the sampling weights in lme().
> You can correct for the biased sampling if you put the variables that
> affect the weights in as predictors in the model. Cluster sampling could
> perhaps then be modelled as another level of random effect.
I've been struggeling with case weights (in the case of unequal
selection probabilities) in mixed effects models. Those are not
possible in lme(). Isn't it, however, possible to use case weights in
glmmPQL from MASS?
Koen Pelleriaux
Sociologist
University of Antwerp