Quantifying individual variation in behaviour: mixed-effect modelling approaches
TLDR
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 is provided.Abstract:
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.read more
Citations
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Factors Influencing Individual Variation in Farm Animal Cognition and How to Account for These Statistically.
TL;DR: The latest developments on the causes of individual variation in cognitive outcomes, such as the choice of cognitive test, sex, breed, age, early life environment, rearing conditions, personality, diet, and the animal's microbiome are considered.
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Testing Hypotheses in Ecoimmunology Using Mixed Models: Disentangling Hierarchical Correlations
TL;DR: This work uses simulated data to demonstrate that mixed models allow for proper partitioning of (co)variances, and demonstrates that conventional statistical tools grossly misestimate relevant parameters, which urges caution in relating ecoimmunological hypotheses to existing empirical research.
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Early‐breeding females experience greater telomere loss
TL;DR: Using historical data from a long‐term study population of dark‐eyed juncos (Junco hyemalis), it is found that telomere loss between years was greater in earlier breeding females, regardless of chronological age, and that environmental conditions could be the primary cause of accelerated telomeres loss in early breeders.
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Yolk steroids in great tit Parus major eggs: variation and covariation between hormones and with environmental and parental factors.
TL;DR: It is shown for the first time that yolk hormone levels are related to ambient temperature in the day(s) just before laying and, in the last-laid egg, with the day it is laid relative to the onset of incubation, and that the concentrations of pairs of yolk hormones can vary with each other in a different way between and within clutches.
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Pesticide-induced changes in personality depend on the urbanization level
TL;DR: It is found that the pesticide treatment changed the average activity and the behavioural covariation (activity and boldness), but not the behavioural repeatability, and suggests that pollution may play an important role in understanding the evolution and maintenance of animal personalities in natural populations.
References
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Introduction to quantitative genetics
TL;DR: The genetic constitution of a population: Hardy-Weinberg equilibrium and changes in gene frequency: migration mutation, changes of variance, and heritability are studied.
Book
Mixed-Effects Models in S and S-PLUS
TL;DR: Linear Mixed-Effects and Nonlinear Mixed-effects (NLME) models have been studied in the literature as mentioned in this paper, where the structure of grouped data has been used for fitting LME models.
Journal Article
Human biochemical genetics
TL;DR: For the next few weeks the course is going to be exploring a field that’s actually older than classical population genetics, although the approach it’ll be taking to it involves the use of population genetic machinery.
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Multilevel analysis : an introduction to basic and advanced multilevel modeling
Tom A. B. Snijders,Roel Bosker +1 more
TL;DR: In this paper, the authors proposed a multilevel regression model to estimate within-and between-group correlations using a combination of within-group correlation and cross-group evidence.
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Generalized linear mixed models: a practical guide for ecology and evolution
Benjamin M. Bolker,Mollie Elizabeth Brooks,Connie J. Clark,Shane W. Geange,John R. Poulsen,M. Henry H. Stevens,Jada-Simone S. White +6 more
TL;DR: The use (and misuse) of GLMMs in ecology and evolution are reviewed, estimation and inference are discussed, and 'best-practice' data analysis procedures for scientists facing this challenge are summarized.