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Bayesian Linear Regression in JASP

Hello everyone.

I performed a Bayesian Linear Regression in JASP. but I do not know how to read the result table. What does P(M)、 P(M丨data)、BFm 、BF10 mean?What are their values indicating that the model fits well?

Thank you very much in advance,



  • Dear Hongxia,

    This is briefly described here (for the case of ANOVA):

    We have almost finished a paper explaining these concepts for regression in more detail.


    1. We have R^2 in the table, but the next version (a week away) will have more fit diagnostics. Note that the measures who wanted to know about are all *relative* measures.
    2. P(M) = prior model probability; P(M|data) = posterior model probability; BF_M = change from prior model odds to posterior model odds; BF10 = Bayes factor for each row (model) against the one on top (this is why the first BF = 1).



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