Comment by nonbel

6 years ago

This is mostly right, but you are still thinking of these rejections as "false positives" for some reason. They are real deviations from the null hypothesis ("true positives"). The problem is the user didn't test the null model they wanted, it is 100% user error.

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nonbel

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dwaltrip  6 years ago

Can you explain that last sentence? What is a valid null model if everything is correlated?

  • nonbel  6 years ago

    A model of whatever process you think generated the data.

    EDIT:

    I guess I should say that the concept of testing a "null model" without interpreting the fit relative to other models is wrong to begin with. You need to use Bayes' rule and determine:

      p(H[0]|D) = p(H[0])p(D|H[0])/sum(p(H[0:n])*p(D|H[0:n]))

    Lots of stuff wrong with what has been standard stats for the last 70 years, it literally amounts to stringing together a bunch of fallacies and makes no sense at all.