*[From the preprint “Abandoning statistical significance is both sensible and practical” by Valentin Amrhein, Andrew Gelman, Sander Greenland, and Blakely McShane*

###### “Dr Ioannidis writes against our proposals to abandon statistical significance…”

###### “…we disagree that a statistical significance-based “filtering process is useful to avoid drowning in noise” in science and instead view such filtering as harmful.”

###### “First, the implicit rule to not publish nonsignificant results biases the literature with overestimated effect sizes and encourages “hacking” to get significance.”

###### “Second, nonsignificant results are often wrongly treated as zero.”

###### “Third, significant results are often wrongly treated as truth rather than as the noisy estimates they are, thereby creating unrealistic expectations of replicability.”

###### “Fourth, filtering on statistical significance provides no guarantee against noise. Instead, it amplifies noise because the quantity on which the filtering is based (the *p*-value) is itself extremely noisy and is made more so by dichotomizing it.”

###### “We also disagree that abandoning statistical significance will reduce science to “a state of statistical anarchy.” Indeed, the journal *Epidemiology* banned statistical significance in 1990 and is today recognized as a leader in the field.”

###### “The replication crisis in science is not the product of the publication of unreliable findings. … Rather, the replication crisis has arisen because unreliable findings are presented as reliable*.”*

###### To read more, **click here**.

**click here**