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The autologistic actor attribute model, or ALAAM, is the social influencecounterpart of the better-known exponential-family random graph model (ERGM)for social selection. Extensive experience with ERGMs has shown that theproblem of near-degeneracy which often occurs with simple models can beovercome by using "geometrically weighted" or "alternating" statistics. In themuch more limited empirical applications of ALAAMs to date, the problem ofnear-degeneracy, although theoretically expected, appears to have been less ofan issue. In this work I present a comprehensive survey of ALAAM applications,showing that this model has to date only been used with relatively smallnetworks, in which near-degeneracy does not appear to be a problem. I shownear-degeneracy does occur in simple ALAAM models of larger empirical networks,define some geometrically weighted ALAAM statistics analogous to those forERGM, and demonstrate that models with these statistics do not suffer fromnear-degeneracy and hence can be estimated where they could not be with thesimple statistics.

Overcoming near-degeneracy in the autologistic actor attribute model