Category: ASA Guide to P-values

(Excerpts from) ‘P-Value Thresholds: Forfeit at Your Peril’ (free access)

A key recognition among those who write on the statistical crisis in science is that the pressure to publish attention-getting articles can incentivize researchers to produce eye-catching but inadequately scrutinized claims. We may see much the same sensationalism in broadcasting metastatistical research, especially if it takes the form of scapegoating or banning statistical significance. A […]

Palavering about Palavering about P-values

Nathan Schachtman (who was a special invited speaker at our recent Summer Seminar in Phil Stat) put up a post on his law blog the other day (“Palavering About P-values”) on an article by a statistics professor at Stanford, Helena Kraemer. “Palavering” is an interesting word choice of Schachtman’s. Its range of meanings is relevant […]

The NEJM Issues New Guidelines on Statistical Reporting: Is the ASA P-Value Project Backfiring?

The New England Journal of Medicine NEJM announced new guidelines for authors for statistical reporting  yesterday. The ASA describes the change as “in response to the ASA Statement on P-values and Statistical Significance and subsequent The American Statistician special issue on statistical inference” (ASA I and II, in my abbreviation) If so, it seems to have backfired. I don’t […]

B. Haig: The ASA’s 2019 update on P-values and significance (ASA II)(Guest Post)

Brian Haig, Professor Emeritus Department of Psychology University of Canterbury Christchurch, New Zealand The American Statistical Association’s (ASA) recent effort to advise the statistical and scientific communities on how they should think about statistics in research is ambitious in scope. It is concerned with an initial attempt to depict what empirical research might look like in “a […]

“The 2019 ASA Guide to P-values and Statistical Significance: Don’t Say What You Don’t Mean” (Some Recommendations)

Some have asked me why I haven’t blogged on the recent follow-up to the ASA Statement on P-Values and Statistical Significance (Wasserstein and Lazar 2016)–hereafter, ASA I. They’re referring to the editorial by Wasserstein, R., Schirm, A. and Lazar, N. (2019) –hereafter, ASA II–opening a special on-line issue of over 40 contributions responding to the […]

If you like Neyman’s confidence intervals then you like N-P tests

Neyman, confronted with unfortunate news would always say “too bad!” At the end of Jerzy Neyman’s birthday week, I cannot help imagining him saying “too bad!” as regards some twists and turns in the statistics wars. First, too bad Neyman-Pearson (N-P) tests aren’t in the ASA Statement (2016) on P-values: “To keep the statement reasonably […]

If you like Neyman’s confidence intervals then you like N-P tests

Neyman, confronted with unfortunate news would always say “too bad!” At the end of Jerzy Neyman’s birthday week, I cannot help imagining him saying “too bad!” as regards some twists and turns in the statistics wars. First, too bad Neyman-Pearson (N-P) tests aren’t in the ASA Statement (2016) on P-values: “To keep the statement reasonably […]

Diary For Statistical War Correspondents on the Latest Ban on Speech

When science writers, especially “statistical war correspondents”, contact you to weigh in on some article, they may talk to you until they get something spicy, and then they may or may not include the background context. So a few writers contacted me this past week regarding this article (“Retire Statistical Significance”)–a teaser, I now suppose, […]