If my sample is just barely large enough to detect my main effect, the smallest interaction that I can reasonably expect is a knockout effect.
Interaction analyses – Interpreting effect sizes (part 2)
Interaction analyses – Power (part 1)
In this series I try to convey a couple of insights about power for interactions in linear regressions. First, how to do a power analysis for a interaction in a linear regression (this post), then interpreting the effect size of a interaction (part 2), and finally thinking about how large (or small) an effect size it is reasonable to plan for (part 3).