2009
DOI: 10.1016/j.anbehav.2008.11.006
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A simple method for distinguishing within- versus between-subject effects using mixed models

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Cited by 795 publications
(731 citation statements)
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“…Because we were interested in separating the within-and among-family effects of chirp duration on chirp rate, two separate predictor variables were derived for each male from the chirp duration measures [46,47]: mean family chirp duration (the mean of the male's family) and within-family deviation in chirp duration (the male's deviation from the family mean). The models included chirp rate as the dependent variable and four fixed factors: mean family chirp duration, within-family deviation in chirp duration, nutritional environment and the interaction between mean family chirp duration and nutritional environment.…”
Section: Methodsmentioning
confidence: 99%
“…Because we were interested in separating the within-and among-family effects of chirp duration on chirp rate, two separate predictor variables were derived for each male from the chirp duration measures [46,47]: mean family chirp duration (the mean of the male's family) and within-family deviation in chirp duration (the male's deviation from the family mean). The models included chirp rate as the dependent variable and four fixed factors: mean family chirp duration, within-family deviation in chirp duration, nutritional environment and the interaction between mean family chirp duration and nutritional environment.…”
Section: Methodsmentioning
confidence: 99%
“…For a locally adapted trait, it would even be possible to differentiate markers explaining among-population phenotypic variability (by testing for among-population effects) from markers explaining within-population variability (by testing for within-population effects). The technique of within-group centring (Davis et al, 1961;van de Pol and Wright, 2009) could be used to this end. It simply consists in distinguishing between the mean-population effect and the within-population effect of each predictor of an association model, as follows:…”
Section: What Is the Use Of Common Garden Experiments In The Genomic Era?mentioning
confidence: 99%
“…The application of mixed models to longitudinal data has bypassed this major limitation and revealed that within-and between-individual effects can differ in many situations and that both can result in a positive association between age and trait expression at the population level (van de Pol and Verhulst 2006;van de Pol and Wright 2009;Rebke et al 2010). Most longitudinal studies published to date have analyzed key life-history traits, such as reproductive success (e.g., Dugdale et al 2011;Froy et al 2013) and survival (e.g., Bouwhuis et al 2012), but there is growing interest in age-dependent variation in secondary sexual traits (Balbontín et al 2011;Evans et al 2011) and behavior (Mainguy and Côté 2008;Nussey et al 2009).…”
Section: Introductionmentioning
confidence: 99%
“…However, only longitudinal studies can separate within-individual (i.e., phenotypic plasticity, individual improvement, senescence) and between-individual (i.e., selective appearance or disappearance of certain phenotypes) effects of age on trait expression (van de Pol and Verhulst 2006;van de Pol and Wright 2009). As individual trajectories can be hidden by demographic heterogeneity (Bouwhuis et al 2009;van de Pol and Wright 2009;Evans et al 2011), neglecting within-individual effects might lead to incorrect conclusions about the effects of aging on life histories.…”
Section: Introductionmentioning
confidence: 99%