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How to explain BFinclusion for regression analyses?


I am using JASP for Bayesian Regression analyses. To report bayes factors for each factor in my model, I used the "Effects" box and get a BFinclusion value for every factor. I am struggling with how to report these factors and how to explain what these numbers mean. Is it correct to say that this is the average effect of including the respective factor over all possible models given the factors included in my regression analysis?

Thanks in advance!


  • Hi Elien,

    This topic occasionally pops up on this forum, so searching for the relevant terms will bring up some relevant posts. As you suggest, the BF inclusion is the change from prior to posterior odds, where the odds concern all the models with a predictor of interest to all models without that predictor. So it is a BF for including a predictor averaged across the models under consideration.


    Thanked by 1elienbellon
  • Thank you, EJ!

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