The DOI matches its Crossref record; 77 of the 77 references it cites were found in a registry or an index.
Avoiding the misuse of BLUP in behavioural ecology
Open accessAbstract
Having recognized that variation around the population-level “Golden Mean” of labile traits contains biologically meaningful information, behavioural ecologists have focused increasingly on exploring the causes and consequences of individual variation in behaviour. These are exciting new directions for the field, assisted in no small part by the adoption of mixed-effects modelling techniques that enable the partitioning of among- and within-individual behavioural variation. It has become commonplace to extract predictions of individual random effects from such models for use in subsequent analyses (for example, between a personality trait and other individual traits such as cognition, physiology, or fitness-related measures). However, these predictions are made with large amounts of error that is not carried forward, rendering further tests susceptible to spurious P values from these individual-level point estimates. We briefly summarize the problems with such statistical methods that are used regularly by behavioural ecologists, and highlight the robust solutions that exist within the mixed model framework, providing tutorials to aid in their implementation.
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Cites
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That BLUP is a Good Thing: The Estimation of Random Effects
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Personality and the emergence of the pace-of-life syndrome concept at the population level
Réale, D., Garant, D., Humphries, M. M., Bergeron, P., Careau, V., & Montiglio, P.-O. (2010) · Philosophical Transactions of the Royal Society B: Biological Sciences · doi:10.1098/rstb.2010.0208 · Cited by 1,446
Quantifying individual variation in behaviour: mixed‐effect modelling approaches
Dingemanse, N. J., & Dochtermann, N. A. (2013) · Journal of Animal Ecology · doi:10.1111/1365-2656.12013 · Cited by 1,081
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Self-citationGuidelines for estimating repeatability
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Cited by
A brief introduction to mixed effects modelling and multi-model inference in ecology
Harrison, X. A., Donaldson, L., Correa-Cano, M. E., Evans, J., Fisher, D. N., Goodwin, C. E. D., Robinson, B. S., Hodgson, D. J., & Inger, R. (2018) · PeerJ · doi:10.7717/peerj.4794 · Cited by 2,094
Northrup, J. M., Vander Wal, E., Bonar, M., Fieberg, J., Laforge, M. P., Leclerc, M., Prokopenko, C. M., & Gerber, B. D. (2022) · Ecological Applications · doi:10.1002/eap.2470 · Cited by 227
“…mean resource availability and the point estimates (β coefficient) from the selection functions (e.g., Northrup et al. 2016), which fail to appropriately propagate parameter uncertainty, leading to inappropriate variance in the functional response (Hadfield et al. 2010, Houslay and Wilson 2017).”
Background
Metadata
- Authors
- Houslay, T. M., & Wilson, A. J.
- Venue
- Behavioral Ecology
- Publisher
- Oxford University Press (OUP)
- Published
- 2017-03-02
- Volume
- 28
- Issue
- 4
- Pages
- 948-952
- ISSN
- 1045-2249 (ISSN-L)
- 1465-7279
- OpenAlex
- W2592003945
- Cited by
- 312
- References
- 77
- FWCI
- 24.06
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Houslay, T. M., & Wilson, A. J. (2017). Avoiding the misuse of BLUP in behavioural ecology. Behavioral Ecology. https://doi.org/10.1093/beheco/arx023
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
