Simulation Results In our setup, the covariates included in the outcome model are correlated with both the outcome and exposure; hence adjust- ment for these confounding factors can reduce bias and RMSE. Bias in estimation, average model standard error, empirical standard error, RMSE reduction, power, and coverage are provided in Table ?? ; full simulation results are given in Section 3 in supplementary material. Results are averaged across all 64 observational scenarios with standard deviations across scenarios in parentheses. Averaged across all simulation replications and variants, inclusion of covariates in outcome and propensity score models led to reduction in bias and gains in efficiency. We also find that a single covariate, the node’s number of affected neighbors at baseline ( X $^{(9)}$), provides a reduction in RMSE comparable to variable selection approach. As an additional sen- sitivity analysis, we repeated these simulations for larger networks, each larger than those specified here by six-fold, and obtained similar results. The covariates selected in a stepwise procedure for inclusion in the outcome model vary across the different simulated datasets. To assess which covariates are most useful for adjustment in the outcome model, we measure the frequency of covariate inclusion and its variability by simulation scenario (see Figure 2). Degree ( X $^{(1)}$) and covariates related to contagion at baseline (covariates X (9) − X $^{(12)}$) are included most often; others are selected in a range of frequencies. The outcomes models for the two exposure groups are similar. Covariate Selection Table 3: Exposure effect statistics averaged across each simulation characteristic, adjusted for all confounding factors. Each row displays a metric, and each column displays an adjustment feature or strategy for the outcome model. Standard deviations across scenarios are shown in parentheses. None X (9) X $^{(1)}$, . . . , X(10) Stepwise Bias 0.007 -0.024 -0.032 -0.034 Estimated SE 1.82 1.09 0.86 0.86 Empirical Bootstrap SE 1.5 0.95 0.86 0.86 Improvement 0(0) 34(25) 39(22) 39(23) Power 59.6 87.1 90.2 90.6 Coverage 96(2) 97(2) 95(2) 95(2) 13