Register for an account


Enter your name and email address below.

Your email address is used to log in and will not be shared or sold. Read our privacy policy.


Website access code

Enter your access code into the form field below.

If you are a Zinio, Nook, Kindle, Apple, or Google Play subscriber, you can enter your website access code to gain subscriber access. Your website access code is located in the upper right corner of the Table of Contents page of your digital edition.


Is It Time To "Redefine Statistical Significance"?

Neuroskeptic iconNeuroskepticBy NeuroskepticOctober 3, 2017 5:33 PM


Sign up for our email newsletter for the latest science news


A new paper in Nature Human Behaviour has generated lots of debate. In Redefine Statistical Significance, authors Daniel J. Benjamin and colleagues suggest changing the convention that p-values below 0.05 are called 'significant'. Instead, they suggest, the cut-off should be set at 0.005 - a stricter criterion. Over at The Brains Blog, John Schwenkler organized a discussion of the Benjamin et al. proposal, featuring commentary from several statisticians and researchers. One of the commentaries is mine. In it, I don't directly address the merits of p<0.005, but I point out that the p<0.05 rule is a holdover from a very different time. p<0.05 was introduced in 1925, back when statistical tests were carried out by hand. Today, with the help of stats software, we can perform thousands of tests, producing thousands of p-values, in the time it used to take to calculate just one of them. Given a dataset we can carry out many analyses and see which gives the lowest p-values. This is the problem of p-hacking. At p<0.05, 1 in 20 p-values will be significant by chance alone. I'm not sure that a p<0.005 threshold is the best or only solution to this problem. I have long advocated a different and more radical change to how science is carried out: study preregistration. Yet I would be happy to see p<0.005 (or even less) become the norm for non-preregistered studies. Preregistration, I think, would allow us to continue using p<0.05 in the spirit in which it was originally intended: to test significance in a carefully thought out, pre-planned analysis.

    3 Free Articles Left

    Want it all? Get unlimited access when you subscribe.


    Already a subscriber? Register or Log In

    Want unlimited access?

    Subscribe today and save 70%


    Already a subscriber? Register or Log In