National Institute of Statistical Sciences (NISS)

Invitation to discuss the ASA Task Force on Statistical Significance and Replication

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The latest salvo in the statistics wars comes in the form of the publication of The ASA Task Force on Statistical Significance and Replicability, appointed by past ASA president Karen Kafadar in November/December 2019. (In the ‘before times’!) Its members are:

Linda Young, (Co-Chair), Xuming He, (Co-Chair) Yoav Benjamini, Dick De Veaux, Bradley Efron, Scott Evans, Mark Glickman, Barry Graubard, Xiao-Li Meng, Vijay Nair, Nancy Reid, Stephen Stigler, Stephen Vardeman, Chris Wikle, Tommy Wright, Karen Kafadar, Ex-officio. (Kafadar 2020)

The full report of this Task Force is in the The Annals of Applied Statistics, and on my blogpost. It begins:

In 2019 the President of the American Statistical Association (ASA) established a task force to address concerns that a 2019 editorial in The American Statistician (an ASA journal) might be mistakenly interpreted as official ASA policy. (The 2019 editorial recommended eliminating the use of “p < 0.05” and “statistically significant” in statistical analysis.) This document is the statement of the task force… (Benjamini et al. 2021)

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Categories: 2016 ASA Statement on P-values, ASA Task Force on Significance and Replicability, JSM 2020, National Institute of Statistical Sciences (NISS), statistical significance tests

Is it impossible to commit Type I errors in statistical significance tests? (i)

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While immersed in our fast-paced, remote, NISS debate (October 15) with J. Berger and D. Trafimow, I didn’t immediately catch all that was said by my co-debaters (I will shortly post a transcript). We had all opted for no practice. But  looking over the transcript, I was surprised that David Trafimow was indeed saying the answer to the question in my title is yes. Here are some excerpts from his remarks: Continue reading

Categories: D. Trafimow, J. Berger, National Institute of Statistical Sciences (NISS), Testing Assumptions

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