Weighted Empirical Adaptive Variance Estimators for Correlated Data Regression

These are standard error estimators for generalised linear models fitted to correlated data that extend the model-robust sandwich estimators used by Huber for independent data and Liang and Zeger for longitudinal data. All of these estimators are described in
Lumley T., Heagerty P.J. (1999) ``Weighted Empirical Adaptive Variance Estimators for Correlated Data Regression'' JRSS B 61:2;459-479
The most complete version is a tarred and gzipped R package. It can be used in S-PLUS as well by unpacking, sourcing the file R/glmweave.R and copying the S help files from .Data/.Help to your .Data/.Help directory. Windows users may prefer the zipped version. I don't know how to set this up as an S-PLUS for Windows library -- if you do I would be grateful to be told -- but it has all the components. The functions (with links to HTML documentation) are The functions contain no compiled code, so they are easy to install on a variety of systems.

I also have Stata code for the Newey-West estimator for generalised linear models (glmnewey.ado,glmnewey.hlp), but not yet for the WEAVE estimators.

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