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I have made available on my web page some software for fitting
(generalized bilinear) mixed effects regression models for
dyadic network data. The software is written for the R statistical
programming environment. Some of the options for the model fitting
procedure are given at the bottom of this email. The software, some
examples using Poisson and logistic regression, and a preprint
detailing the model estimation procedures are available at:
Department of Statistics
University of Washington
Seattle, WA 98195
* Y is a square (nxn) sociomatrix. Missing (at random) data is allowed.
* Xd is an nxnxrd array giving dyad-specific covariates.
* Xs is an nxrs matrix of sender-specific covariates.
* Xs is an nxrr matrix of receiver-specific covariates.
Model specification arguments (defaults in parentheses):
* family ("gaussian") : can be "gaussian", "poisson" or "binomial"
* directed (T) : logical denoting if the relation is directed or not.
* k (0) : an integer denoting the dimension of the inner-product
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