How to interpret model with “main effect 1 + main effect 2 + main effect 1*main effect 2"?
I have got a model which has two independent variables (IV):
Group: Explorers vs. Time Controls (between-subjects)
Season: Summer 1, Autumn, Winter, Spring, Summer 2 (within-subjects)
In JASP's Bayesian RM ANOVA this shows me that this model has the most support:
Group + Season + Group*Season (BF10=870).
The closest single main effect model is Season (BF=190).
How do I interpret the Group + Season + Group*Season model correctly?
I've read this blogpost https://www.cogsci.nl/blog/interpreting-bayesian-repeated-measures-in-jasp
And I've read Part I and Part II of the JASP papers for psychology but I'm not sure how to make sense of this model.