Comments (3)
Correct me if I misunderstood this: you are interested in the variation between networks (e.g., in terms of the number of adopters), rather than in the variation between nodes nested in a single network (i.e., on some nodal attribute). If that sounds about right, then TNAM is not for you. TNAM models the diffusion within a network at the level of nodes, possibly over time.
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I think you could just use a GLM framework in this case, e.g., a Poisson regression for count data, to model the number of adopters per network as a function of network-level characteristics. The reason is that the networks are independent from each other, which means the i.i.d. assumption is not violated. Good luck!
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