Changing philosophies and tools for statistical inferences in behavioral ecology

Garamszegi, Zsolt, Calhim, Sara, Dochtermann, Ned, Hegyi, Gergely, Hurd, Peter L., Jorgensen, Christian, Kutsukake, Nobuyuki, Lajeunesse, Marc J., Pollard, Kimberly A., Schielzeth, Holger, Symonds, Matthew R.E. and Nakagawa, Shinichi 2009, Changing philosophies and tools for statistical inferences in behavioral ecology, Behavioral ecology, vol. 20, no. 6, pp. 1363-1375, doi: 10.1093/beheco/arp137.

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Title Changing philosophies and tools for statistical inferences in behavioral ecology
Author(s) Garamszegi, Zsolt
Calhim, Sara
Dochtermann, Ned
Hegyi, Gergely
Hurd, Peter L.
Jorgensen, Christian
Kutsukake, Nobuyuki
Lajeunesse, Marc J.
Pollard, Kimberly A.
Schielzeth, Holger
Symonds, Matthew R.E.ORCID iD for Symonds, Matthew R.E.
Nakagawa, Shinichi
Journal name Behavioral ecology
Volume number 20
Issue number 6
Start page 1363
End page 1375
Total pages 13
Publisher Oxford University Press
Place of publication Cary, NC
Publication date 2009
ISSN 1045-2249
Keyword(s) BeStat
Bonferroni correction
frequentist approach
information theoretic approach
measurement error
model selection
P value
statistical power
Summary Recent developments in ecological statistics have reached behavioral ecology, and an increasing number of studies now apply analytical tools that incorporate alternatives to the conventional null hypothesis testing based on significance levels. However, these approaches continue to receive mixed support in our field. Because our statistical choices can influence research design and the interpretation of data, there is a compelling case for reaching consensus on statistical philosophy and practice. Here, we provide a brief overview of the recently proposed approaches and open an online forum for future discussion ( From the perspective of practicing behavioral ecologists relying on either correlative or experimental data, we review the most relevant features of information theoretic approaches, Bayesian inference, and effect size statistics. We also discuss concerns about data quality, missing data, and repeatability. We emphasize the necessity of moving away from a heavy reliance on statistical significance while focusing attention on biological relevance and effect sizes, with the recognition that uncertainty is an inherent feature of biological data. Furthermore, we point to the importance of integrating previous knowledge in the current analysis, for which novel approaches offer a variety of tools. We note, however, that the drawbacks and benefits of these approaches have yet to be carefully examined in association with behavioral data. Therefore, we encourage a philosophical change in the interpretation of statistical outcomes, whereas we still retain a pluralistic perspective for making objective statistical choices given the uncertainties around different approaches in behavioral ecology. We provide recommendations on how these concepts could be made apparent in the presentation of statistical outputs in scientific papers.
Language eng
DOI 10.1093/beheco/arp137
Field of Research 060201 Behavioural Ecology
Socio Economic Objective 970106 Expanding Knowledge in the Biological Sciences
HERDC Research category C1.1 Refereed article in a scholarly journal
Copyright notice ©2009, Oxford University Press
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