Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Statistics, statistical thinking, and the IACUC

To improve rigor and reproducibility of animal research, the recently released NIH Advisory Committee report recommends major improvements in investigator statistical training and practice. The IACUC can serve as important gatekeepers of research quality by ensuring that simple statistically based reproducibility criteria are addressed in animal use protocols.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

References

  1. 1.

    Reynolds, P. S. & Garvan, C. W. Miltary Medicine 185, 85–95 (2020).

    Google Scholar 

  2. 2.

    Macleod, M. R. & Mohan, S. ILAR J. 60, 17–23 (2020).

    Article  Google Scholar 

  3. 3.

    Freedman, L. P., Cockburn, I. M. & Simcoe, T. S. PLoS Biol. 13, e1002165 (2015).

    Article  Google Scholar 

  4. 4.

    Tong, C. American Statistician 73, 246–261 (2019).

    Article  Google Scholar 

  5. 5.

    Silverman, J., Macy, J. & Preisig, P. Lab. Animal (NY) 46, 129–135 (2017).

    Article  Google Scholar 

  6. 6.

    Preece, D. A. Utilitas Mathematica 21, 201–244 (1982).

    Google Scholar 

  7. 7.

    Brønstad, A. et al. Laboratory Animals 50, 1–20 (2016).

    Article  Google Scholar 

  8. 8.

    Everitt, J. I. & Berridge, B. R. ILAR J. 58, 129–137 (2017).

    CAS  Article  Google Scholar 

  9. 9.

    Macleod, M. R. et al. PLOS Biology 13, e1002301 (2015).

    Article  Google Scholar 

  10. 10.

    Olsson, I. A. F., Varga, O. & Sandøe, P. ALTEX Proceedings 4, 33–36 (2015).

    Google Scholar 

  11. 11.

    Sena, E. S. & Currie, G. L. Animal Welfare 28, 107–115 (2019).

    Article  Google Scholar 

  12. 12.

    Bateson, P. New Scientist 109, 30–32 (1986).

    PubMed  Google Scholar 

  13. 13.

    Mohan, S., Barbee, R. W. & Silk, S. B. J. Am Assoc. Lab. Anim. Sci. 57, 104–109 (2018).

    PubMed  PubMed Central  Google Scholar 

  14. 14.

    MacCallam, C. J. PLoS Biol. 8, e1000413 (2010).

    Article  Google Scholar 

  15. 15.

    Altman, D. G. BMJ 281, 1182–1184 (1980).

    CAS  Article  Google Scholar 

  16. 16.

    Würbel, H. Lab. Anim. (NY) 46, 164–166 (2017).

    Article  Google Scholar 

  17. 17.

    Cox, D. R. Annals of Applied Statistics 1, 1–16 (2007).

    Article  Google Scholar 

  18. 18.

    Russell, W.M.S. & Burch, R.L. The Principles of Humane Experimental Technique, (1959).

  19. 19.

    Vetter, T. R. & Mascha, E. J. Anesth Analg 125, 678–681 (2017).

    Article  Google Scholar 

  20. 20.

    Preece, D. A. R. A. Biometrics 46, 925–935 (1990).

    Article  Google Scholar 

  21. 21.

    Henderson, V. C., Kimmelman, J., Fergusson, D., Grimshaw, J. M. & Hackam, D. G. PLoS Med. 10, e1001489 (2013).

    Article  Google Scholar 

  22. 22.

    Vollert, J. et al. BMJ Open Science 4, e100046 (2020).

    Article  Google Scholar 

  23. 23.

    Fitzpatrick, B. G., Koustova, E. & Wang, Y. Lab. Anim. (NY) 47, 175–177 (2018).

    Article  Google Scholar 

  24. 24.

    Schulz, K. F. & Grimes, D. A. Lancet 365, 1348–1353 (2005).

    Article  Google Scholar 

  25. 25.

    Reynolds, P. S. Lab. Anim. (NY) 48, 249–253 (2019).

    Article  Google Scholar 

Download references

Author information

Affiliations

Authors

Corresponding author

Correspondence to Penny Reynolds.

Ethics declarations

Competing interests

The authors declare no competing interests.

Supplementary Information

Supplementary Information

APPENDIX: STUDY PLANNING AND DESIGN RESOURCES.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Reynolds, P. Statistics, statistical thinking, and the IACUC. Lab Anim 50, 266–268 (2021). https://doi.org/10.1038/s41684-021-00832-w

Download citation

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing