Computational protocol: Oxidative Stress Mediates Physiological Costs of Begging in Magpie (Pica pica) Nestlings

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Protocol publication

[…] For statistical analyses, we performed Generalized Linear Mixed Effects Models of Restricted Maximum Likelihood (REML-GLMM) by using the package “nlme” in R . In each model, nest of origin was introduced as a random factor to control for variance among nests, thus avoiding pseudoreplication . We checked for the interaction between nest and treatment, which in all cases proved non-significant, and thus was removed from final models. The lack of a significant interaction implies that the effect of treatment was independent from that of nest. We included date of sampling as a covariate in every model, given that time of storage may affect enzymatic activity and protein concentration , and date may affect variables such as immune response and MDA concentration . Given that immune response, mass gained, MDA level, and treatment are supposed to be interrelated, when we search for the effect of treatment on MDA level, we controlled for immune response and mass gained, introduced as covariate. Similarly, in an additional model we looked for the relationship between MDA level and begging time, controlling for immune response and mass gained. For every model, we checked for homogeneity of variances (Levene’s test), and for normality of residuals by using the Kolmogorov-Smirnov test . Means are given with their standard error (SE). […]

Pipeline specifications

Software tools lme4, nlme
Application Mathematical modeling