The simulation-based procedure for the power calculation of data-driven network analysis. This procedure consists three steps: i) simulate M brain connectome data sets under H_1; ii) perform statistical inference; iii) calculate the power as the proportion of successfully rejecting the null hypothesis in ii) for all M datasets. The power calculation for the network outcome is determined by the sample size S, level of significance alpha, and effect sizes (Cohen's $d$ or $f^2$), which are the same as univariate cases. Additionally, users need to specify the network-specific parameters, such as $N, |V_c|, \rho_0, \rho_1$. In accordance with Helwegen et al. , these required parameters are used to characterize the ``network organization". In addition, to better approximate the statistical power, the number of repetitions $K$ and permutation tests $M$ also helps determine the quality of obtained power.