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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,

Hongxia

Comments

  • Dear Hongxia,

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

    https://link.springer.com/content/pdf/10.3758%2Fs13423-017-1323-7.pdf

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

    Furthermore:

    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).

    Cheers,

    E.J.

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