Adjust p-values in gof.ergm.ego() for uncertainty in estimates of GoF statistics.

[krivit]

This is challenging, since the the statistics are assumed to be approximately normal under egocentric sampling, whereas the simulated statistic distribution is estimated empirically. It is not clear, in particular whether for a simulated (univariate) statistic vector sim.stat, and obs.stat.est and obs.stat.stderr egocentrically inferred statistics, the better "p-value" is

min(mean(pnorm(sim.stat, obs.stat.est, obs.stat.stderr)),
    mean(pnorm(sim.stat, obs.stat.est, obs.stat.stderr, lower.tail=FALSE)))

or

mean(pmin(pnorm(sim.stat, obs.stat.est, obs.stat.stderr),
          pnorm(sim.stat, obs.stat.est, obs.stat.stderr, lower.tail=FALSE)))

or if neither is valid.