Hostname: page-component-cd9895bd7-fscjk Total loading time: 0 Render date: 2024-12-25T18:03:06.940Z Has data issue: false hasContentIssue false
  • English
  • Français

Statistical power, effect size and animal welfare: recommendations for good practice

Published online by Cambridge University Press:  01 January 2023

D Hawkins ,
E Gallacher  and
M Gammell
D Hawkins*
Affiliation:
Animal & Environmental Research Group, Department of Life Sciences, Anglia Ruskin University, East Road, Cambridge CB1 1PT, UK
E Gallacher
Affiliation:
Animal & Environmental Research Group, Department of Life Sciences, Anglia Ruskin University, East Road, Cambridge CB1 1PT, UK Imperial College, Silwood Park Campus, Ascot, Berkshire SL5 7TG, UK
M Gammell
Affiliation:
Department of Life & Physical Sciences, Galway-Mayo Institute of Technology, Dublin Road, Galway, Ireland
*
* Contact for correspondence and requests for reprints: dawn.hawkins@anglia.ac.uk
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

Despite the particular relevance of statistical power to animal welfare studies, we noticed an apparent lack of sufficient information reported in papers published in Animal Welfare to facilitate post hoc calculation of statistical power for use in meta-analyses. We therefore conducted a survey of all papers published in Animal Welfare in 2009 to assess compliance with relevant instructions to authors, the level of statistical detail reported and the interpretation of results regarded as statistically non-significant. In general, we found good levels of compliance with the instructions to authors except in relation to the level of detail reported for the results of each test. Although not requested in the instructions to authors, exact P-values were reported in just over half of the tests but effect size was not explicitly reported for any test, there was no reporting of a priori statistical analyses to determine sample size and there was no formal assessment of non-significant results in relation to type II errors. As a first stage to addressing this we recommend more reporting of a priori power analyses, more comprehensive reporting of the results of statistical analysis and the explicit consideration of possible statistical power issues when interpreting P-values. We also advocate the calculation of effect sizes and their confidence intervals and a greater emphasis on the interpretation of the biological significance of results rather than just their statistical significance. This will enhance the efforts that are currently being made to comply with the 3Rs, particularly the principle of reduction.

Keywords

animal welfareeffect sizenon-significancesample sizestatistical powertype II error
Type
Research Article
Information
Animal Welfare , Volume 22 , Issue 3 , August 2013 , pp. 339 - 344
Copyright
© 2013 Universities Federation for Animal Welfare

References

AHVLA 2013 Animal Health and Veterinary Laboratories Agency. http://www.defra.gov.uk/ahvla-en/science/using-animals/Google Scholar
Cohen, J 1988 Statistical Power Analysis for the Behavioural Sciences. Academic Press: New York, USAGoogle Scholar
Cohen, J 1992 A power primer. Quantative Methods in Psychology 112: 155–159Google ScholarPubMed
Colegrave, N and Ruxton, G 2003 Confidence intervals are a more useful complement to non-significant tests than are power calculations. Behavioural Ecology 14: 446–450. http://dx.doi.org/10.1093/beheco/14.3.446CrossRefGoogle Scholar
EFSA Scientific Committee 2011 Statistical significance and biological relevance. EFSA Journal: 2372–2389. www.efsa.europa.eu/efsajournalGoogle Scholar
Ellis, P 2010 The Essential Guide to Effect Sizes: Statistical Power, Meta-Analysis, and the Interpretation of Research Results. Cambridge University Press: Cambridge, UK. http://dx.doi.org/10.1017/CB09780511761676CrossRefGoogle Scholar
Faul, F, Erdfelder, E, Buchner, A and Lang, A-G 2009 Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses. Behavior Research Methods 4: 1149–1160. http://dx.doi.org/10.3758/BRM.41.4.1149CrossRefGoogle Scholar
Hawkins, D 2009 Biomeasurement, Second Edition. Oxford University Press: Oxford, UKGoogle Scholar
Hoenig, J and Heisey, D 2001 The abuse of power: the pervasive fallacy of power calculations for data analysis. The America Statistican 55: 19–24. http://dx.doi.org/10.1198/000313001300339897CrossRefGoogle Scholar
Jennions, M and Møller, P 2003 A survey of the statistical power of research in behavioural ecology and animal behaviour. Behavioural Ecology 14: 438–445CrossRefGoogle Scholar
Kilkenny, C, Parsons, N, Kadyszewski, E, Festing, MFW, Cuthill, IC, Fry, D, Hutton, J and Altman, DG 2009 Survey of the quality of experimental design, statistical analysis and reporting of research using animals. PLoS ONE 4: e7824. http://dx.doi.org/10.1371/journal.pone.0007824CrossRefGoogle Scholar
Morrison, L 2007 Assessing the reliability of ecological monitoring data: power analysis and alternative approaches. Natural Areas Journal 27: 83–91. http://dx.doi.org/10.3375/0885-8608(2007)27[83:ATROEM]2.0.CO;2CrossRefGoogle Scholar
Nakagawa, S and Cuthill, I 2007 Effect size, confidence interval and statistical significance: a practical guide for biologists. Biological Reviews 82: 591–605. http://dx.doi.org/10.1111/j.1469-185X.2007.00027.xCrossRefGoogle ScholarPubMed
Nature Medicine 2005 Statistically significant (editorial). Nature Medicine 11: 1. http://dx.doi.org/10.1038/nm0105-1CrossRefGoogle Scholar
Philips, C 2005 Meta-analysis: a systematic and quantitative review of animal experiments to maximize the information derived. Animal Welfare 14: 333–338Google Scholar
Smith, D, Hardy, I and Gammell, M 2011 Power rangers: no improvement in the statistical power of analyses published in Animal Behaviour. Animal Behaviour 81: 347–352. http://dx.doi.org/10.1016/j.anbehav.2010.09.026CrossRefGoogle Scholar
Sokal, R and Rolf, F 2012 Biometry: The Principles and Practice of Statistics in Biological Research, Fourth Edition. WH Freeman and Company: New York, USAGoogle Scholar
Thomas, L and Juanes, F 1996 The importance of statistical power analysis: an example from Animal Behaviour. Animal Behaviour 52: 856–859. http://dx.doi.org/10.1006/anbe.1996.0232CrossRefGoogle Scholar