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Before posting new reflections on where we are 5 years after the ASA P-value controversy–both my own and readers’–I will reblog some reader commentaries from 2022 in connection with my (2022) editorial in Conservation Biology: “The Statistical Wars and Intellectual Conflicts of Interest”. First, here are excerpts from my editorial: Continue reading
les stats, c’est moi
This is the last of the selected posts I will reblog from 5 years ago on the 2019 statistical significance controversy. The original post, published on this blog on December 13, 2019, had 85 comments, so you might find them of interest. I invite readers to share their thoughts as to where the field is now, in relation to that episode, and to alternatives being used as replacements for statistical significance tests. Use the comments and send me guest posts. Continue reading
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I continue my selective 5-year review of some of the posts revolving around the statistical significance test controversy from 2019. This post was first published on the blog on November 14, 2019. I feared then that many of the howlers of statistical significance tests would be further etched in granite after the ASA’s P-value project, and in many quarters this is, unfortunately, true. One that I’ve noticed quite a lot is the (false) supposition that negative results are uninformative. Some fields, notably psychology, keep to a version of simple Fisherian tests, ignoring Neyman-Pearson (N-P) tests (never minding that Jacob Cohen was a psychologist who gave us “power analysis”). (See note [1]) For N-P, “it is immaterial which of the two alternatives…is labelled the hypothesis tested” (Neyman 1950, 259). Failing to find evidence of a genuine effect, coupled with a test’s having high capability to detect meaningful effects, warrants inferring the absence of meaningful effects. Even with the simple Fisherian test, failing to reject H0 is informative. Null results figure importantly throughout science, such as when the ether was falsified by Michelson-Morley, and in directing attention away from unproductive theory development.
Please share your comments on this blogpost. Continue reading
I continue my 5-year review of some highlights from the “abandon significance” movement from 2019. This post was first published on this blog on November 30, 2019, It was based on a call by then American Statistical Association President, Karen Kafadar, which sparked a counter-movement. I will soon begin sharing a few invited guest posts reflecting on current thinking either on the episode or on statistical methodology more generally. I may continue to post such reflections over the summer, as they come in, so let me know if you’d like to contribute something. Share your thoughts in the comments.
Mayo writing to Kafadar
I never met Karen Kafadar, the 2019 President of the American Statistical Association (ASA), but the other day I wrote to her in response to a call in her extremely interesting June 2019 President’s Corner: “Statistics and Unintended Consequences“:
I only recently came across her call, and I will share my letter below. First, here are some excerpts from her June President’s Corner (her December report is due any day). Continue reading
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Soon after the Wasserstein et al (2019) “don’t say significance” editorial, John Ioannidis invited Andrew Gelman and I to write editorials from our different perspectives on an associated editorial that Nature invited. It was written by Amrhein, Greenland and McShane (AGM, 2019). Prior to the publication of AGM 2019, people were given the opportunity to add their names to the Nature article.
A campaign followed that aimed at the collection of signatures in what was called a ‘petition’ on the widely popular blogsite of Andrew Gelman. Ultimately, 854 scientists signed the petition and the list of their names was published along with commentary. (Hardwicke and Ioannidis, 2019, p. 2)
Tom Hardwicke and John Ioannidis (2019) took advantage of the opportunity “to perform a survey of the signatories to understand how and why they signed the endorsement” (ibid.). This post, reblogged from September 25 2019, includes all 3 articles: the survey by Hardwicke and Ioannidis, and the editorials by Gelman and I. They appeared in the European Journal of Clinical Investigations (2019). I’m still interested in reader responses (in the comments) to the question I pose. Continue reading
Experts convene to explore new philosophy of statistics field
Error Statistics Philosophy 