USING STATISTICS: Spotting and Avoiding Them
Suggestions for Reviewers, Referees, Editors (and
of Institutional Review Boards)
- Base acceptance on on the quality of
implementation, analysis, and writing (as well as the importance of the
questions being studied), but not
on the results of the analysis
- See Suggestions
- Have authors followed these guidelines?
- See Suggestions for
- Is the paper written to facilitate
- How would a
reader following these guidelines rate the research?
- Is the research "reproducible"? That is, is
information given in the paper and the material referenced in the paper
adequate for someone to duplicate the data gathering and analysis?
- Check to be sure power
calculations are prospective, not retrospective.
- As needed, join with others to help promote
practices" in research and publication.
- Consult the references below for more
J. Coyne (2009), Are most positive findings in health
psychology false ... or at least somewhat exaggerated?, European Health
Psychologist, Vol. 11, No. 3, pp. 49 - 51.
J. P. A. Ioannidis (2008) Why most discovered true associations are
inflated, Epidemiology vol 19
(5), 640 - 648.
C. Kilkenny et al, Improving
Bioscience Research Reporting: The ARRIVE Guidelines for Reporting
Animal Research, PLoS Biol
Peer-to-Peer blog Blog for peer reviewers and about peer review
Medicine Editors (2005) Minimizing Mistakes and Embracing Uncertainty,
PLoS Med 2(8): e272, doi:10.1371/journal.pmed.0020272. This is an
editorial response to the Ioannis article mentioned in the Introduction to this website.