  The autologistic actor attribute model (ALAAM) is a model for social
influence, derived from the more widely known exponential-family random graph
model (ERGM). ALAAMs can be used to estimate parameters corresponding to
multiple forms of social contagion associated with network structure and actor
covariates. This work introduces ALAAMEE, open-source Python software for
estimation, simulation, and goodness-of-fit testing for ALAAM models. ALAAMEE
implements both the stochastic approximation and equilibrium expectation (EE)
algorithms for ALAAM parameter estimation, including estimation from snowball
sampled network data. It implements data structures and statistics for
undirected, directed, and bipartite networks. We use a simulation study to
assess the accuracy of the EE algorithm for ALAAM parameter estimation and
statistical inference, and demonstrate the use of ALAAMEE with empirical
examples using both small (fewer than 100 nodes) and large (more than 10 000
nodes) networks.
