# How can I apply a power analysis on an interaction in order to show that even if I test more participants, I'll never get the effect ?

The interaction is not significant but I need to show that it is not a matter of a lack of power. What is the simplest way to do so?

## Popular Answers

Gabor Borgulya· St George's, University of LondonA remark on "never getting the effect": if there is a statistical interaction or not depends on the measurement scales of the (two or more) predictors the interaction of is studied. For example if two continuous variables are NOT in interaction using their original scales, then their log transformed variants will be in interaction. So in my opinion showing no interaction also means finding the appropriate measurement scales.

If you have the appropriate measurement scales you can declare that there is no interaction if you powered your study for equivalence and the study results confirmed it; alternatively you can declare that "you will never get the effect" if your power analysis demonstrates that showing the interaction with a test for difference would require a sample size that is practically infeasible.

Power analyses are performed before data collection. The wording "is not significant" suggests that you may already have the data. In this case look at the confidence interval after appropriate transformations and compare it to the relevance thresholds.

Jamie I D Campbell· University of SaskatchewanYou could also use MorePower 6.0 (Campbell & Thompson, 2012). MorePower 6.0 computes sample size, effect size and power statistics for a specified ANOVA effect. It also calculates confidence intervals for the effect based on formulas from Jarmasz and Hollands (2009), as well as Bayesian posterior probabilities for the null and alternative hypotheses using the Bayesian Information Criterion (Masson, 2011; Wagenmakers, 2007). The program affords a straightforward comparison of these alternative approaches to interpretation of ANOVA. MorePower 6.0 is freely available at https://wiki.usask.ca/pages/viewpageattachments.action?pageId=420413544

The MorePower calculator is very easy to use, but let me know if you have any questions.

Cheers

Jamie

Campbell, J. I. D., & Thompson, V. A. (2012). MorePower 6.0 for ANOVA with relational confidence intervals and Bayesian analysis. Behavior Research Methods, 44, 1255-1265. doi: 10.3758/s13428-012-0186-0