I'm reading the following paper on non-parametric standard errors and tests for network statistics - https://www.stats.ox.ac.uk/~snijders/Snijders_Borgatti.pdf by Snijders & Borgatti.
When comparing e.g. the density of two networks, we can calculate a t-statistic using the formula:
Where Z1 and Z2 are the observed densities of each network, and SE1 and SE2 are the standard errors derived from bootstrapped samples of each network.
My question is, to generate a p-value for this t-statistic, what degrees of freedom should we be using (in the example they cite, network 1 has an N of 16 vertices, and network 2 an N of 15 vertices)? Is it analogous to the Student's t-test, so df = N1+N2-2 ?