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JASP: H-measure priors (in BLR classification performance)

Hi, I was wondering if you can explain or point me to what are the priors used in the H-measure (in Binary Logistic Regression, classification performance metrics)?

thank you



  • Hi Martin,

    Can you post a screenshot, so I know exactly what you are referring to?


  • Hi EJ, sorry for losing track of this post, see the red circles in the enclosed figure (it is in the binary logistic regression)

  • Hi Martin,

    Ah, this is an analysis I am not expert on. But I do know it is a frequentist analysis. So is the H-measure a Bayesian concept? I will ask Erik-Jan (no, this is not strange).


  • Hi Martin,

    the H-measure performance metric is "just another" measure of classification performance. For more information about this H-measure you can read the paper by its developer David Hand. For a slightly more approachable introduction I suggest the website

    Hope this helps!


  • Thank you Erik-Jan, yes I'm just trying to understand how exactly the weights are assigned to the TP/TN versus FP/FN (for, the standard accuracy measure clearly is very biased for unbalanced classes, as is often the case in medicine..).
    Thank you for the link!

    EJ > I've had a could very "bayesian" students in my lab for a few years, and now that JASP exists, well, that's all they talk about (other than "how big" their Bayes Factor is.. :-) :-) :-) )

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