Power Rules: Practical Statistical Power Calculations

Recent work emphasizes the importance of statistical power and shows that power in the social sciences tends to be extremely low. In this paper, I offer simple rules that make statistical power more approachable for substantive researchers. The rules describe how researchers can compute power using (1) features of a reference population, (2) an existing study with a similar design and outcome, and/or (3) a pilot study. In the case of balanced, between-subjects designs (perhaps controlling for pre-treatment variables), these rules are sufficient for a complete and compelling power analysis for treatment effects and interactions using only paper-and-pencil. For more complex designs, these rules can provide a useful ballpark prediction before turning to specialized software or complex simulations. Most importantly, these rules help researchers develop a sharp intuition about statistical power. For example, it can be helpful for readers and researchers to know that experiments have 80\% power to detect effects that are 2.5 times larger than the standard error and how to easily form a conservative prediction of the standard error using pilot data. These rules lower the barrier to entry for researchers new to thinking carefully about statistical power and help researchers design powerful, informative experiments.