The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Quantifying individual variation in behaviour: mixed‐effect modelling approaches
Open accessAbstract
Summary: Growing interest in proximate and ultimate causes and consequences of between‐ and within‐individual variation in labile components of the phenotype – such as behaviour or physiology – characterizes current research in evolutionary ecology. The study of individual variation requires tools for quantification and decomposition of phenotypic variation into between‐ and within‐individual components. This is essential as variance components differ in their ecological and evolutionary implications. We provide an overview of how mixed‐effect models can be used to partition variation in, and correlations among, phenotypic attributes into between‐ and within‐individual variance components. Optimal sampling schemes to accurately estimate (with sufficient power) a wide range of repeatabilities and key (co)variance components, such as between‐ and within‐individual correlations, are detailed. Mixed‐effect models enable the usage of unambiguous terminology for patterns of biological variation that currently lack a formal statistical definition (e.g. ‘animal personality’ or ‘behavioural syndromes’), and facilitate cross‐fertilisation between disciplines such as behavioural ecology, ecological physiology and quantitative genetics.
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Cites
Mixed-Effects Models in S and S-PLUS
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Repeatability for Gaussian and non-Gaussian data: a practical guide for biologists.
Nakagawa, S., & Schielzeth, H. (2010) · Biological Reviews · doi:10.1111/j.1469-185x.2010.00141.x · Cited by 2,584
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Cited by
Habituation and sensitization: new thoughts about old ideas
Blumstein, D. T. (2016) · Animal Behaviour · doi:10.1016/j.anbehav.2016.05.012 · Cited by 426
Dammhahn, M., Dingemanse, N. J., Niemelä, P. T., & Réale, D. (2018) · Behavioral Ecology and Sociobiology · doi:10.1007/s00265-018-2473-y · Cited by 319
Self-citationAvoiding the misuse of BLUP in behavioural ecology
Houslay, T. M., & Wilson, A. J. (2017) · Behavioral Ecology · doi:10.1093/beheco/arx023 · Cited by 312
Debecker, S., & Stoks, R. (2019) · Ecological Monographs · doi:10.1002/ecm.1332 · Cited by 72
Camprasse, E. C. M., Sutton, G. J., Berlincourt, M., & Arnould, J. P. Y. (2017) · Marine Biology · doi:10.1007/s00227-017-3193-y · Cited by 27
Metadata
- Authors
- Dingemanse, N. J., & Dochtermann, N. A.
- Venue
- Journal of Animal Ecology
- Publisher
- Wiley
- Published
- 2012-11-21
- Volume
- 82
- Issue
- 1
- Pages
- 39-54
- ISSN
- 0021-8790 (ISSN-L)
- 1365-2656
- OpenAlex
- W2009172303
- Cited by
- 1,081
- References
- 5
- FWCI
- 51.02
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Dingemanse, N. J., & Dochtermann, N. A. (2013). Quantifying individual variation in behaviour: mixed‐effect modelling approaches. Journal of Animal Ecology. https://doi.org/10.1111/1365-2656.12013
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