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When choosing the timing of cross-sectional network snapshots in longitudinalsocial network studies, the effect on the precision of parameter estimatesgenerally plays a minor role. Often the timing is opportunistic or determinedby a variety of considerations such as organizational constraints, funding, andavailability of study participants. Theory to guide the timing of networksnapshots is also missing. We use a statistical framework to relate the timingto the precision of the parameter estimates, specifically, the sum of therelative widths of their confidence intervals. We illustrate thiscomputationally using the STERGM suite of the statnet package to estimate theparameters of the network dynamics. Analytically, we derive simpleapproximations for the optimal timing when the parameters correspond to therates for different network events. We find that the optimal time depends themost on the network processes with short expected durations and few expectedevents such as the dissolution of ties. We apply our approximations to a simpleexample of a dynamic network with formation and dissolution of iid ties.

Optimal timing of cross-sectional network samples in longitudinal network studies