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      Meta-analysis challenges a textbook example of status signalling and demonstrates publication bias

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          Abstract

          The status signalling hypothesis aims to explain within-species variation in ornamentation by suggesting that some ornaments signal dominance status. Here, we use multilevel meta-analytic models to challenge the textbook example of this hypothesis, the black bib of male house sparrows ( Passer domesticus). We conducted a systematic review, and obtained primary data from published and unpublished studies to test whether dominance rank is positively associated with bib size across studies. Contrary to previous studies, the overall effect size (i.e. meta-analytic mean) was small and uncertain. Furthermore, we found several biases in the literature that further question the support available for the status signalling hypothesis. We discuss several explanations including pleiotropic, population- and context-dependent effects. Our findings call for reconsidering this established textbook example in evolutionary and behavioural ecology, and should stimulate renewed interest in understanding within-species variation in ornamental traits.

          eLife digest

          Many bird species have colourful, intricately patterned plumage. This ornamentation is generally believed to exist to attract partners. In the 1970s, however, scientists proposed an alternative idea, called the ‘status signalling hypothesis’. This suggests that some birds have plumage ornaments that indicate the fighting abilities or dominance status of their bearers, much like the military badges worn by humans. These badges of status might evolve because fights, which commonly determine who gets valuable resources such as food, are a risky business. Individuals would greatly benefit from being able to predict the fighting abilities of any potential competitor and so avoid fights that they will probably lose.

          Male house sparrows have a black patch on their throat, known as the bib, that has been considered to be a textbook demonstration of the status signalling hypothesis. However, most of the studies that support this idea studied small numbers of birds and used inconsistent methods. Furthermore, some recent studies have failed to replicate previous findings.

          Sánchez-Tójar et al. collected data from several house sparrow populations across the world and systematically scrutinized the published literature to find all of the studies that tested the status signalling hypothesis in house sparrows. This revealed only weak evidence that the bib of male house sparrows signals the fighting abilities of its bearer. Instead, the published literature is a biased subsample; failures to replicate the hypothesis likely remain unpublished.

          Currently, failures to replicate previous findings are generally deemed uninteresting, and so are not often published. By demonstrating the need to replicate findings robustly to avoid biasing conclusions, Sánchez-Tójar et al. thus join the call for a change in incentives and scientific culture.

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          Effect size, confidence interval and statistical significance: a practical guide for biologists.

          Null hypothesis significance testing (NHST) is the dominant statistical approach in biology, although it has many, frequently unappreciated, problems. Most importantly, NHST does not provide us with two crucial pieces of information: (1) the magnitude of an effect of interest, and (2) the precision of the estimate of the magnitude of that effect. All biologists should be ultimately interested in biological importance, which may be assessed using the magnitude of an effect, but not its statistical significance. Therefore, we advocate presentation of measures of the magnitude of effects (i.e. effect size statistics) and their confidence intervals (CIs) in all biological journals. Combined use of an effect size and its CIs enables one to assess the relationships within data more effectively than the use of p values, regardless of statistical significance. In addition, routine presentation of effect sizes will encourage researchers to view their results in the context of previous research and facilitate the incorporation of results into future meta-analysis, which has been increasingly used as the standard method of quantitative review in biology. In this article, we extensively discuss two dimensionless (and thus standardised) classes of effect size statistics: d statistics (standardised mean difference) and r statistics (correlation coefficient), because these can be calculated from almost all study designs and also because their calculations are essential for meta-analysis. However, our focus on these standardised effect size statistics does not mean unstandardised effect size statistics (e.g. mean difference and regression coefficient) are less important. We provide potential solutions for four main technical problems researchers may encounter when calculating effect size and CIs: (1) when covariates exist, (2) when bias in estimating effect size is possible, (3) when data have non-normal error structure and/or variances, and (4) when data are non-independent. Although interpretations of effect sizes are often difficult, we provide some pointers to help researchers. This paper serves both as a beginner's instruction manual and a stimulus for changing statistical practice for the better in the biological sciences.
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            A Nonparametric “Trim and Fill” Method of Accounting for Publication Bias in Meta-Analysis

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              Methodological issues and advances in biological meta-analysis

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                Author and article information

                Contributors
                Role: Reviewing Editor
                Role: Senior Editor
                Journal
                eLife
                Elife
                eLife
                eLife
                eLife Sciences Publications, Ltd
                2050-084X
                13 November 2018
                2018
                : 7
                : e37385
                Affiliations
                [1 ]deptEvolutionary Biology Group Max Planck Institute for Ornithology SeewiesenGermany
                [2 ]deptDepartment of Life Sciences Imperial College London AscotUnited Kingdom
                [3 ]deptSchool of Biological, Earth and Environmental Sciences University of New South Wales SidneyAustralia
                [4 ]deptDepartment of Animal and Plant Sciences University of Sheffield SheffieldUnited Kingdom
                [5 ]deptDepartment of Animal Behaviour Bielefeld University BielefeldGermany
                [6 ]deptLendület Evolutionary Ecology Research Group, Plant Protection Institute, Centre for Agricultural Research Hungarian Academy of Sciences BudapestHungary
                [7 ]deptDepartment of Behavioural Ecology and Evolutionary Genetics Max Planck Institute for Ornithology SeewiesenGermany
                [8 ]deptMTA-PE Evolutionary Ecology Research Group University of Pannonia VeszprémHungary
                [9 ]deptDepartment of Biology University of Kentucky LexingtonUnited States
                Max-Planck Institute for Evolutionary Biology Germany
                Max-Planck Institute for Evolutionary Biology Germany
                Max-Planck Institute for Evolutionary Biology Germany
                Whitman College United States
                Author notes
                [†]

                Department of Evolutionary Biology, Bielefeld University, Bielefeld, Germany.

                [‡]

                Department de Biologia Evolutiva, Ecologia i Ciències Ambientals, University of Barcelona, Barcelona, Spain.

                [§]

                Biodiversity, Macroecology and Biogeography, University of Goettingen, Goettingen, Germany.

                Author information
                http://orcid.org/0000-0002-2886-0649
                http://orcid.org/0000-0002-7765-5182
                https://orcid.org/0000-0001-7197-2278
                http://orcid.org/0000-0002-9558-1201
                http://orcid.org/0000-0002-2136-5346
                http://orcid.org/0000-0002-7505-5458
                http://orcid.org/0000-0001-5163-8096
                https://orcid.org/0000-0003-3848-1244
                Article
                37385
                10.7554/eLife.37385
                6234027
                30420005
                bdda1e3c-50e2-4f23-af26-834383ad8c08
                © 2018, Sánchez-Tójar et al

                This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

                History
                : 09 April 2018
                : 11 October 2018
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100004189, Max-Planck-Gesellschaft;
                Award ID: Open-access funding
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100004189, Max-Planck-Gesellschaft;
                Award ID: Funding captive house sparrow population
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000001, National Science Foundation;
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000270, Natural Environment Research Council;
                Award ID: NE/N013832/1
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100001663, Volkswagen Foundation;
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100010665, H2020 Marie Skłodowska-Curie Actions;
                Award ID: CIG PCIG12-GA-2012-333096
                Award Recipient :
                The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
                Categories
                Research Article
                Ecology
                Custom metadata
                Meta-analysis takes down a textbook example in behavioural and evolutionary ecology, and demonstrates the existence of biases in the current scientific publishing culture.

                Life sciences
                passer domesticus,badge of status,meta-analysis,dominance,ornament,publication bias,other
                Life sciences
                passer domesticus, badge of status, meta-analysis, dominance, ornament, publication bias, other

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