Monthly Archives: May 2022

D. Mayo & D. Hand: “Statistical significance and its critics: practicing damaging science, or damaging scientific practice?”

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Prof. Deborah Mayo, Emerita
Department of Philosophy
Virginia Tech

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Prof. David Hand
Department of Mathematics Statistics
Imperial College London

Statistical significance and its critics: practicing damaging science, or damaging scientific practice?  (Synthese)

[pdf of full paper.] Continue reading

Categories: Error Statistics | 3 Comments

Paul Daniell & Yu-li Ko commentaries on Mayo’s ConBio Editorial

I had been posting commentaries daily from January 6, 2022 (on my editorial “The Statistics Wars and Intellectual conflicts of Interest”, Conservation Biology) until Sir David Cox died on January 18, at which point I switched to some memorial items. These two commentaries from what Daniell calls my ‘birthday festschrift’ were left out, and I put them up now. (Links to others are below.)

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Categories: Mayo editorial, stat wars and their casualties | 1 Comment

3 Commentaries on my Editorial are being published in Conservation Biology

 

 

There are 3 commentaries soon to be published in Conservation Biology on my editorial, “The statistics wars and intellectual conflicts of interest” also published in Conservation Biology. Continue reading

Categories: Mayo editorial, significance tests | Tags: , , , , | Leave a comment

A statistically significant result indicates H’ (μ > μ’) when POW(μ’) is low (not the other way round)–but don’t ignore the standard error

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1. New monsters. One of the bizarre facts of life in the statistics wars is that a method from one school may be criticized on grounds that it conflicts with a conception that is the reverse of what that school intends. How is that even to be deciphered? That was the difficult task I set for myself in writing Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars (CUP, 2008) [SIST 2018]. I thought I was done, but new monsters keep appearing. In some cases, rather than see how the notion of severity gets us beyond fallacies, misconstruals are taken to criticize severity! So, for example, in the last couple of posts, here and here, I deciphered some of the better known power howlers (discussed in SIST Ex 5 Tour II) I’m linking to all of this tour (in proofs). Continue reading

Categories: power, reforming the reformers, SIST, Statistical Inference as Severe Testing | 16 Comments

Do “underpowered” tests “exaggerate” population effects? (iv)

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You will often hear that if you reach a just statistically significant result “and the discovery study is underpowered, the observed effects are expected to be inflated” (Ioannidis 2008, p. 64), or “exaggerated” (Gelman and Carlin 2014). This connects to what I’m referring to as the second set of concerns about statistical significance tests, power and magnitude errors. Here, the problem does not revolve around erroneously interpreting power as a posterior probability, as we saw in the fallacy in this post. But there are other points of conflict with the error statistical tester, and much that cries out for clarification — else you will misunderstand the consequences of some of today’s reforms.. Continue reading

Categories: power, reforming the reformers, SIST, Statistical Inference as Severe Testing | 16 Comments

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