Why is it so difficult to correct the scientific record in sports science? In the first installment in this series of guest posts, Matthew Tenan, a data scientist with a PhD in neuroscience, began the story of how he and some colleagues came to scrutinize a paper. In the second, he explained what happened next. In today’s final installment, he reflects on the editors’ response and what he thinks it means for his field.
In refusing to retract the Dankel and Loenneke manuscript we showed to be mathematically flawed, the editors referred to “feedback from someone with greater expertise” and included the following:
Why is it so difficult to correct the scientific record in sports science? In the first installment in this series of guest posts, Matthew Tenan, a data scientist with a PhD in neuroscience, began the story of how he and some colleagues came to scrutinize a paper. In this post, he explains what happened next.
Two years ago, following heated debate, a sports science journal banned a statistical method from its pages, and a different journal — which had published a defense of that method earlier — decided to boost its statistical chops. But as Matthew Tenan, a data scientist with a PhD in neuroscience relates in this three-part series, that doesn’t seem to have made it any easier to correct the scientific record. Here’s part one.
As it happened, I knew that paper, and I had also expressed concerns about it – when I reviewed it before publication as one of the members of the journal’s editorial board. Indeed, I was brought on to the editorial board of Sports Medicine because the journal had recently received a lot of bad press for publishing a paper about another “novel statistical method” with significant issues and I had been a vocal critic of the sports medicine and sport science field developing their own statistical methods that are not used outside of the field and validated by the wider statistics community.
