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COMMENTARY
Department of Molecular and Cellular Physiology, University of Cincinnati College of Medicine, Cincinnati, Ohio
Address for reprint requests and other correspondence: B. Mackenzie, Dept. of Molecular and Cellular Physiology, Univ. of Cincinnati College of Medicine, PO Box 670576, Cincinnati, OH 45267-0576 (e-mail: bryan.mackenzie{at}uc.edu)
DOUGLAS CURRAN-EVERETT, DALE BENOS, and the editors of the American Physiological Society journals are to be commended for their efforts to raise the standards of statistics reporting in physiology journals. I read with interest the followup (in this issue) to the 2004 guidelines (2), and I am glad to see those efforts sustained. Curran-Everett and Benos reported that "the mere publication of the guidelines failed to impact reporting practices" (at least with regard to the use of standard deviations, confidence intervals, and precise P values), but I offer that it is still too early to assess. Change comes about slowly. If investigators fully embraced the guidelines, which include guidelines on planning the study and establishing the critical significance level 
, we should only now begin to see significant change in the resulting publications. Still, there are those who remain to be persuaded.
As I have talked with colleagues about the 2004 guidelines, the issue of standard deviation versus standard error has drawn the strongest reaction, so I am pleased that this is given special attention in the followup. Figure 1 there illustrates that the sample standard deviation (s, SD), but not the standard error of the sample mean (SEM), describes the variability within the sample, and your other commentators have more eloquently argued this point than can I. Figure 1 in the followup also reminds us that just how well sample standard deviation approximates the population standard deviation (
) depends on sample size (n); hence, the importance of specifying the value of n despite the common idea that it is not necessary when reporting sample standard deviations. Meanwhile, the utility of SEM in making between-group inferences (when its relationship to confidence intervals is understood) has not been understated (see also Ref. 1).
Investigators may be more readily accepting of the push to report precise P values. I would add that reiterating "not significant" alongside the precise P value may be helpful when accepting the null hypothesis since readers may be accustomed to seeing P values only when they are used to report significant differences.
A common reporting deficiency not discussed in the guidelines is the omission of the absolute value of the 100% or control value (and a measure of its variability) in the presentation of normalized data. Adding it to the figure legend is no difficult task, and its inclusion is necessary for other investigators in planning future studies.
While some may disagree with specific recommendations in the guidelines and others may fear them too prescriptive, the guidelines for reporting statistics certainly have physiologists talking more about statistics in general. That's good. Perhaps the wider benefit will be to promote statistics literacy within our discipline. After all, the literature contains more egregious statistical errors than error bar deficiencies, and such errors spring faulty conclusions. The guidelines now need to be backed by efforts on at least two fronts. The first is in better educating our students. A new graduate course "Statistical Methods in Physiology" at this institution is set to become part of the core curricula for our PhD programs in physiology, systems biology, neuroscience, and pharmacology and our MS program in physiology. I hope that other institutions are giving the same priority to statistics courses. The second is in the review process. Tom Lang, in his commentary, places the ball squarely in the court of editors when he "doubt[s] that anything will change until journals stop accepting manuscripts in which the statistics are incorrectly reported." Editors need to provide reviewers explicit permission to call attention to errors in statistical analysis or reporting in manuscripts under review, and editors should weigh such criticisms as they would criticisms of the biology or experimental approach. I suspect that it is presently all too easy for authors to dismiss criticisms concerning statistics, as in the example cited by one of the commentators in the followup. We need to be reminded that careful statistical analyses are not icing; they are central to reaching valid and unbiased conclusions.
REFERENCES
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