Quantifying individual variation in reaction norms: how study design affects the accuracy, precision and power of random regression models

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An approach to estimate short‐term, long‐term and reaction norm repeatability (2015, background): “Bias, or inaccuracy, reflects the level of disagreement between the model’s estimate and the ‘true’ value (e.g. Van de Pol 2012).”
Using repeatability to study physiological and behavioural traits: Ignore time-related change at your peril (2015, background): “…most studies of labile traits reporting R measure about 30 individuals twice each (Alison M. Bell, et al., 2009; Nespolo & Franco, 2007; Wolak, et al., 2012), which is clearly insufficient to detect individual differences in slopes with power or precision (Martin, et al., 2011; van de Pol, 2012).”
Quantifying individual variation in behaviour: mixed-effect modelling approaches. (2013, background): “Martin et al. (2011) and van de Pol (2012) recently discussed sample size requirements for the estimation of intercept-slope correlations (rind0;ind1 ) and provide software for sampling optimization for several variance components.”