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Old 05-17-2018, 06:31 PM
Dr T Non-Fan Dr T Non-Fan is offline
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Default MBI, or Magnitude-Based Inference -- pseudo-stats?

I don't know enough about statistics to prove that "scientists" who use this will wrongly get favorable results to their further their cause.

Maybe someone here, or a study by the AAA or SOA, can help?
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Old 05-23-2018, 03:54 PM
AMedActuary AMedActuary is offline
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I think the article does a pretty good job of summarizing the issues. NHST shouldn't be considered the gold standard either as this article seems to imply but it is good to compare the two. With small sample sizes, it is best to follow Gelman's advice at the end of the article to focus on data quality and pool different study's data together to come to a better conclusion.
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Old 05-24-2018, 01:35 PM
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whoanonstop whoanonstop is offline
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Replacing crap with crap doesn't do much.

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Old 05-24-2018, 01:42 PM
clarinetist clarinetist is offline
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The fact that so many people rely on NHST, the stuff that's described in this article, or the many variations that I've seen on NHST (e.g., Coehn's d, Glass's Delta) to make decisions only shows the lack of understanding that people have when they're performing these computations.

I'm about to finish my masters in stats. I don't think I've run even one hypothesis test throughout my entire career so far. There's a reason for that.

If people care about finding a metric to assess improvement, we could just compare means and be done with it. That is how most of society functions, anyway.
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