Interpreting BF10 and BFM in Bayesian linear regression
I'm new to Bayesian statistics and JASP, and have a question about how to interpret the output from a multiple linear regression. Looking at the BF10, the model with openness as the only predictor is the strongest.
What does the BFM represent? There are three models with BFM > 3, so I am wondering whether I need to interpret this, and if so, how to do it. When I add the other predictors to the null model, the model with openness has a BF10 = 225, but the models with q1sum and q2sum each have BF10s < 1.