Estimation stats launches
In 2018, we wrote a short editorial to introduce new users to estimation graphics. We first released this as a preprint, which was received well.
How best to display data from two groups? Our new@biorxivpreprintargues that the best replacement for t-tests is the Estimation Plot. Unlike older statistical graphics, an estimation plot explicitly visualizes the comparison.https://t.co/EyhYnlsIYdpic.twitter.com/OkJ3B6K4MM
We then submitted this short piece, with the software for consideration by Nature Methods. After some time, and addition of several features, this was accepted and published. The publication was also met with a warm reception by scientists.
The new answer to a 77-year-old problem in data analysis, published today in@naturemethods. Instead of significance tests, use estimation graphics. Our software suite DABEST makes it easy for everyone to visualize effect sizes.https://t.co/UzwXJ7EUC5pic.twitter.com/VtxyY0xaRM
Several other statistics-reform advocates recommended the software for scientists to use in their data analysis. Lewis Halsey, who previously highlighted thevolatilityof p-values, noted that DABEST and theestimationstatsweb app are the best methods to produce publication-quality estimation graphics.
I would really encourage people to check out this website. Easy to use and produces excellent, fully informed between-conditions plots. Far better than standard bar graphs that hide most of the information about your data.#statshttps://t.co/9mqM0T9yWA
Most recently, the Editor-in-Chief of eNeuro, the Society for Neuroscience’s open-access journal, announced that he was changing the journal’s policy to encourage the use of estimation statistics. This was backed up with a greatexplanationof the why and how ofestimationby Robert J. Calin-Jageman and Geoff Cumming. The Editor-in-Chief Christophe Bernard wrote a personal account of how he came to adopt estimation:
#eNeuro@eNeuroEiCannounces new author guidelines for statistical inferencehttps://t.co/8YJSzaSGPY
This is a very promising development. We hope that this policy change at eNeuro spreads further, as we believe journal policy, when paired with the right tools for analysts, is a powerful way to transform statistical practice.