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A survey of the statistical power of research in behavioral ecology and animal behavior

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  • Michael D. Jennions
  • Anders Pape Møller

Abstract

We estimated the statistical power of the first and last statistical test presented in 697 papers from 10 behavioral journals. First tests had significantly greater statistical power and reported more significant results (smaller p values) than did last tests. This trend was consistent across journals, taxa, and the type of statistical test used. On average, statistical power was 13--16% to detect a small effect and 40--47% to detect a medium effect. This is far lower than the general recommendation of a power of 80%. By this criterion, only 2--3%, 13--21%, and 37--50% of the tests examined had the requisite power to detect a small, medium, or large effect, respectively. Neither p values nor statistical power varied significantly across the 10 journals or 11 taxa. However, mean p values of first and last tests were significantly correlated across journals (r =.67, n = 10, p =.034), with a similar trend for mean power (r =.63, n = 10, p =.051). There is therefore some evidence that power and p values are repeatable among journals. Mean p values or power of first and last tests were, however, uncorrelated across taxa. Finally, there was a significant correlation between power and reported p value for both first (r =.13, n = 684, p =.001) and last tests (r =.16, n = 654, p <.0001). If true effect sizes are unrelated to study sample sizes, the average true effect size must be nonzero for this pattern to emerge. This suggests that failure to observe significant relationships is partly owing to small sample sizes, as power increases with sample size. Key words: effect size, meta-analysis, publication bias, sample sizes, statistical power. [Behav Ecol 14:438--445 (2003)] Copyright 2003.

Suggested Citation

  • Michael D. Jennions & Anders Pape Møller, 2003. "A survey of the statistical power of research in behavioral ecology and animal behavior," Behavioral Ecology, International Society for Behavioral Ecology, vol. 14(3), pages 438-445, May.
  • Handle: RePEc:oup:beheco:v:14:y:2003:i:3:p:438-445
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    Cited by:

    1. John A. List, 2024. "Optimally generate policy-based evidence before scaling," Nature, Nature, vol. 626(7999), pages 491-499, February.
    2. Eszter Czibor & David Jimenez‐Gomez & John A. List, 2019. "The Dozen Things Experimental Economists Should Do (More of)," Southern Economic Journal, John Wiley & Sons, vol. 86(2), pages 371-432, October.
    3. Andrés López-Sepulcre & Sebastiano De Bona & Janne K. Valkonen & Kate D.L. Umbers & Johanna Mappes, 2015. "Item Response Trees: a recommended method for analyzing categorical data in behavioral studies," Behavioral Ecology, International Society for Behavioral Ecology, vol. 26(5), pages 1268-1273.
    4. Eliot Abrams & Jonathan Libgober & John A. List, 2020. "Research Registries: Facts, Myths, and Possible Improvements," NBER Working Papers 27250, National Bureau of Economic Research, Inc.
    5. Verniest, Fabien & Greulich, Sabine, 2019. "Methods for assessing the effects of environmental parameters on biological communities in long-term ecological studies - A literature review," Ecological Modelling, Elsevier, vol. 414(C).
    6. Denes Szucs & John P A Ioannidis, 2017. "Empirical assessment of published effect sizes and power in the recent cognitive neuroscience and psychology literature," PLOS Biology, Public Library of Science, vol. 15(3), pages 1-18, March.
    7. Daniele Fanelli, 2012. "Negative results are disappearing from most disciplines and countries," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(3), pages 891-904, March.
    8. Daniele Fanelli, 2010. "Do Pressures to Publish Increase Scientists' Bias? An Empirical Support from US States Data," PLOS ONE, Public Library of Science, vol. 5(4), pages 1-7, April.
    9. Pavel Linhart & Hans Slabbekoorn & Roman Fuchs, 2012. "The communicative significance of song frequency and song length in territorial chiffchaffs," Behavioral Ecology, International Society for Behavioral Ecology, vol. 23(6), pages 1338-1347.

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