Last month, the QUEST center in Berlin organized the first METAxDATA meeting on building automated screening tools for data-driven meta-research. On the first night of the meeting, 13 researchers gave lightning talks about their tools. The clip below features my <2 minute lightning talk about statcheck.
All lightning talks were recorded and can be found here.
My dissertation is finished!
The cover: my own desk, feat. SIPS, BITSS, and COS. Cover design by Niels Bongers.
The contents: statcheck, data sharing, meta-analysis, power, bias, and more.
You can find the full thesis here:
In the latest Science Insider written by Dalmeet Singh Chawla I argue that statcheck does exactly what it’s supposed to do: check the consistency of APA reported NHST results.
Read the entire piece here.
In our new preprint we investigated the validity of statcheck. Our main conclusions were:
- statcheck’s sensitivity, specificity, and overall accuracy are very high. The specific numbers depended on several choices & assumptions, but ranged from:
- sensitivity: 85.3% – 100%
- specificity: 96.0% – 100%
- accuracy: 96.2% – 99.9%
- The prevalence of statistical corrections (e.g., Bonferroni, or Greenhouse-Geisser) seems to be higher than we initially estimated
- But: the presence of these corrections doesn’t explain the high prevalence of reporting inconsistencies in psychology
We conclude that statcheck’s validity is high enough to recommend it as a tool in peer review, self-checks, or meta-research.
Our paper “Journal data sharing policies and statistical reporting inconsistencies in psychology” has been accepted for publication in the open access journal Collabra: Psychology!
The updated (accepted) pre-print can be found on PsyArXiv: https://psyarxiv.com/sgbta.
Publons announced the winner of the Sentinel Award for outstanding advocacy, innovation or contribution to scholarly peer review, and I am proud to announce that statcheck was crowned runner-up!
I am honored that the judges considered statcheck a useful contribution to the peer review system. In the end, one of the things I hope to achieve is that all Psychology journals will consider it standard practice to quickly “statcheck” a paper for statistical inconsistencies to avoid publishing them.
A very warm congratulations to the winner of the award: Irene Hames. Irene spent most of her career on improving the quality of peer review and it is great that her work is recognized in this way! Also congratulations to the rest of the Sentinel Award nominees: Retraction Watch, American Geophysical Union, ORCiD, F1000Research, The Committee on Publication Ethics (COPE), Kyle Martin and Gareth Fraser.
For more information about the award, the winner, and the finalists, see this page.
This week the Guardian’s Science Weekly podcast focuses on statistical malpractice and fraud in science. We talk about the role of statcheck in detecting statistical inconsistencies, and discuss the causes and implications of seemingly innocent rounding errors.
This podcast also offers fascinating insights from consultant anaesthetist John Carlisle about the detection of data fabrication, and president of the Royal Statistical Society David Spiegelhalter about the dangers of statistical malpractice.
Proud to announce that I’ve been shortlisted for the Publon Sentinel Award for my work on statcheck. The Sentinel Award is an award for outstanding advocacy, innovation or contribution to scholarly peer review.
At this point, statcheck is used in the peer review process of two major psychology journals (Psychological Science and the Journal for Experimental Social Psychology) and an increasing number of journals are recommending using statcheck on your own manuscript before submitting it.
For more information about the award and the other great candidates, see this page.
We just published the preprint of our new study “Journal Data Sharing Policies and Statistical Reporting Inconsistencies in Psychology” at https://osf.io/preprints/psyarxiv/sgbta.
In this paper, we ran three independent studies to investigate if data sharing is related to fewer statistical inconsistencies in a paper. Overall, we found no relationship between data sharing and reporting inconsistencies. However, we did find that journal policies on data sharing are extremely effective in promoting data sharing (see the Figure below).
We argue that open data is essential in improving the quality of psychological science, and we discuss ways to detect and reduce reporting inconsistencies in the literature.