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Dear Nick,

for RSiena / stochastic actor-based etwork evolution models, the issue of relative importance of effects (taking into account prevalence of the effect statistic) was addressed - and a solution proposed - in this paper:
Indlekofer, Natalie, and Ulrik Brandes. "Relative importance of effects in stochastic actor-oriented models." Network Science 1.03 (2013): 278-304.
I am not aware of similar work on ERGMs, but the ideas from this paper can to a good degree be transferred to the contribution of effects to tie swap probabilities in an ERGM.

In terms of 'coefficient of determination', I would think it is hard to get a meaningful one. Here is one proposal, relying on spectral analysis / the vector of ordered eigenvalues:
Shore, Jesse, and Benjamin Lubin. "Spectral goodness of fit for network models." Social Networks 43 (2015): 16-27.
The authors claim universality, but similar R-square-type indices can be constructed for any other set of network statistics (triad census, geodesic distribution, degree distributions, etc.)

Best,
Christian


On 19-Mar-16 06:42, Nicholas Harrigan wrote:
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Dear SOCNET,

We are trying to approximate a coefficient of determination for an ERGM (actually the relatively contribution to the coefficient of determination for each of the individual parameters of the ergm).

We would also be happy with something like an effect size, but which took account of the relative prevalence of the graph statistic (since rare statistics may have a big effect, but not a major contribution to a model because of their rarity).

Does any one have suggestions?

We will also want to solve this problem for an RSiena model in the near future, so suggestions for RSiena would be welcome too.

Thanks
Nick


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