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  Advice on comparing two independent samples of circular data in biology.

Landler, L., Ruxton, G. D., & Malkemper, E. P. (2021). Advice on comparing two independent samples of circular data in biology. Scientific Reports, 11(1): 20337. doi:10.1038/s41598-021-99299-5.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0009-6AEC-7 Version Permalink: https://hdl.handle.net/21.11116/0000-0009-6AF1-0
Genre: Journal Article

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This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. Te images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. © The Author(s) 2021
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 Creators:
Landler, Lukas1, Author
Ruxton, Graeme D1, Author
Malkemper, E. Pascal1, 2, Author           
Affiliations:
1External Organizations, ou_persistent22              
2Max Planck Research Group Neurobiology of Magnetoreception, Center of Advanced European Studies and Research (caesar), Max Planck Society, ou_3169318              

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 Abstract: Many biological variables are recorded on a circular scale and therefore need different statistical treatment. A common question that is asked of such circular data involves comparison between two groups: Are the populations from which the two samples are drawn differently distributed around the circle? We compared 18 tests for such situations (by simulation) in terms of both abilities to control Type-I error rate near the nominal value, and statistical power. We found that only eight tests offered good control of Type-I error in all our simulated situations. Of these eight, we were able to identify theWatson's U2 test and aMANOVAapproach, based on trigonometric functions of the data, as offering the best power in the overwhelming majority of our test circumstances. There was often little to choose between these tests in terms of power, and no situation where either of the remaining six tests offered substantially better power than either of these. Hence, we recommend the routine use of either Watson's U2 test or MANOVAapproach when comparing two samples of circular data.

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Language(s): eng - English
 Dates: 2021
 Publication Status: Issued
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 Table of Contents: -
 Rev. Type: Peer
 Identifiers: ISI: 34645855
DOI: 10.1038/s41598-021-99299-5
PMID: 34645855
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Funding program : Austrian Science Fund (P32586 )
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Grant ID : 948728
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Funding organization : European Research Council

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Title: Scientific Reports
  Abbreviation : Sci Rep
Source Genre: Journal
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Publ. Info: London, UK : Nature Publishing Group
Pages: - Volume / Issue: 11 (1) Sequence Number: 20337 Start / End Page: - Identifier: ISSN: 2045-2322
CoNE: https://pure.mpg.de/cone/journals/resource/2045-2322