1. Medicine
  2. Neuroscience
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Statistics: Sex difference analyses under scrutiny

  1. Colby J Vorland  Is a corresponding author
  1. Department of Applied Health Science, Indiana University School of Public Health, United States
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Cite this article as: eLife 2021;10:e74135 doi: 10.7554/eLife.74135
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Considering sex differences in experimental design.

(A) A so-called factorial design permits testing of sex differences. For example, both female (yellow boxes) and male mice (blue boxes) are fed either a treatment diet (green pellets) or control diet (orange pellets). Garcia-Sifuentes and Maney found that 63 % of articles employed a factorial design in at least one experiment with sex as a factor. (B) An appropriate way to statistically test for sex differences is with a two-way analysis of variance (ANOVA). If a statistically significant interaction is observed between sex and treatment, as shown in the figure, evidence for a sex difference is supported. Garcia-Sifuentes and Maney found that in studies using a factorial design, less than one third tested for an interaction between sex and treatment. (C) Performing a statistical test between the treatment and control groups within each sex, and comparing the nominal statistical significance, is not a valid method to look for sex differences. Yet, this method was used in nearly half of articles that used a factorial design and concluded a sex-specific effect.

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