Tutorial: Power Analyses for Interaction Effects in Cross-Sectional Regressions

and associated Shiny apps allow researchers with minimal or no programming experience to perform analytic and simulation-based power analyses for interactions. At minimum, these analyses require the Pearson's correlation between variables and sample size, and additional parameters including reliability and the number of discrete levels that a variable takes (e.g., binary or likert scale) can optionally be specified. In this Tutorial we demonstrate how to perform power analyses using our package and give examples of how power can be impacted by main effects, correlations between main effects, reliability, and variable distributions. We also include a brief discussion of how researchers may select an appropriate interaction effect size when performing a power analysis.