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It was conducted using the lme4 package in R [82].
Analysis was conducted in R 3.4.0 (R Core Development Team 2017), using the lme4 package (Bates et al. 2015).
A multilevel logistic regression model was fit to the data using the lme4 package in R and maximum likelihood Laplace approximation estimation procedures (Bates, Maechler, Bolker, & Walker, 2015).
We analyzed the effects on the binary dependent variable (yes/no answers) with a generalized linear mixed model (with a logit link), using the lme4 package in the R environment.
Parasite sensitivity was evaluated using a Generalized Linear Mixed Model of the Binomial family (Logit) fit by the maximum likelihood, using the lme4 package in R. Parasite gender, macrozone, and antiparasitics were used as fixed factors and farm was the random factor.
Because of the binary response variable (yes or no), we analyzed effects on proportion correct and proportion of yes answers with a generalized mixed effect model (with a logit link), using the lme4 package (Bates, Sarkar, Bates, & Matrix, 2007; Pinheiro, Bates, DebRoy, & Sarkar, 2006) in the R environment (R Development Core Team, 2016).
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We estimated all model parameters using the lme4 packages available in the R statistical software.8 .8
The transport of the optical photons inside the scintillator were simulated by using the Geant4 package.
The inverse transformation was implemented using the SPM8 package.
Normalisation and inverse transformation were implemented using the SPM8 package.
The PCA was performed in R [53] using the ade4 package.
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