Exploring Bayes ANOVA interactions
Having used mostly frequentist statistics thus far, I am unfamiliar with how to explain main effects when there is an interaction when using Bayes factor ANOVA. If, for example, I have an experiment with two robust within-subject main effects, and an interaction between those conditions with a between-subject group factor (conditions A x B x group effect), does it make sense to then perform separate Bayes factor ANOVAs on the individual groups' data to make sense of/explain the triple interaction?
Comments
Yes, that's one way to go. A hard-core Bayesian might want to apply all models at once instead of following a two-step strategy, but in many cases you'd arrive at the same conclusion. In general, the qualitative interpretations ("there is an effect") are the same for the frequentist and the Bayesian paradigm.
E.J.
Thanks for the help! In part the approach relates to what I am trying to show, the initial 3 way interaction is from a scalp-wide analysis of EEG data across all time points in an ERP epoch, and the follow-ups exploring the interaction focus on a subset of specific electrodes to look at the within-subject conditions. I wasn't sure how to approach it other than the frequentist approach.