Output linear regression
Hello, everyone. I would like to firstly apologize for my incipient knowledge of statistics. I have been using JASP to perform bayesian linear regression analyses, but I am finding difficult to interpret the outputs. I am aware that a high BF10 value shows me the strengh of my data, but how do I interpret BFM and %error values? I am sending a screenshot of my analyses and it would be very kind if anyone could help me interpret which is the best model. Thank you very much!
Comments
Dear FLPS,
The interpretation is straightforward: nothing much is going on. The error % provides an indication of the numerical error of approximation relative to the size of what is estimated. The BF_M term compares prior model odds (0.063/(1-0.063)) to the posterior odds (e.g., for the second row, 0.044/(1-0.044)). See also Part II here: https://osf.io/m6bi8/
Cheers,
E.J.