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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.

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