English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Open

A recent proposal to "redefine statistical significance" (Benjamin, et al.Nature Human Behaviour, 2017) claims that false positive rates "wouldimmediately improve" by factors greater than two and replication rates woulddouble simply by changing the conventional cutoff for 'statisticalsignificance' from P<0.05 to P<0.005. I analyze the veracity of these claims,focusing especially on how Benjamin, et al neglect the effects of P-hacking inassessing the impact of their proposal. My analysis shows that once P-hackingis accounted for the perceived benefits of the lower threshold all butdisappear, prompting two main conclusions: (i) The claimed improvements tofalse positive rate and replication rate in Benjamin, et al (2017) areexaggerated and misleading. (ii) There are plausible scenarios under which thelower cutoff will make the replication crisis worse.

Why "Redefining Statistical Significance" Will Not Improve Reproducibility and Could Make the Replication Crisis Worse