I have a question about GEE estimates. First, let me specify a model from a
generalized linear mixed model perspective, more specifically a logistic
regression model with random effects with one within and one between
predictor. The within-cluster (or subject-specific) model is:
logit(y) = b0 + b1(X1)
and the between-cluster (or between subject) models are:
In this model there are two random effects, u0j and u1j(X1).
In GEE framework, I understand there are difference in parameter estimates
(population-averaged vs. cluster-specific) and that the error terms are
handled differently. Within GEE, I know that u0j represents the
within-cluster (or subject-specific) correlated error and is modeled via
the working correlation matrix with specifications appropriate for the
given model such as exchangeable, auto-regressive, etc.
Now my question. What about the second error term, u1j(X1); is this error
simply ignored in the GEE framework or is it somehow modeled within the
working correlation matrix?
Along similar lines, suppose one has a three level logistic model with many
possible error terms if using generalized linear mixed model
(cluster-specific). How are these additional error terms addressed with GEE
estimation?
___________________________________________________________________
Bryan W. Griffin
Curriculum, Foundations, & Reading
P.O. Box 8144
Georgia Southern University
Statesboro, GA 30460-8144
