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The QTL allelic effects are modelled with random coefficient parametric curves and using a gametic relationship matrix.
Geographical variations were modelled with random effects and the significance of variability was assessed using a likelihood ratio test statistic, after taking into account sex, age, time period and a quadratic follow-up temporal trend.
Additional site level variability was modelled with random effects.
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To illustrate the robustness of this behaviour, we repeated the simulation using a smooth exogenous perturbation (e.g., a strong wind, modelled with a random normal variate, smoothed with a Gaussian kernel of eight seconds).
It has been shown that protein-protein interaction networks can efficiently be modelled with the random walk betweenness centrality [ 81] so we were interested to compare the two measures in our experimental setting.
The dynamics of the variables was modelled using linear mixed-effect models with a random intercept and slope and compared [23].
The level 1 intercept was modelled as random, with hospital factors as fixed-effect predictors.
Participant traces were modelled as random effects with varying intercepts [24].
Activity times are modelled as random variables with a β-distribution.
Mutations are Poisson distributed with rate U and their effects modelled as random vectors, from a normal distribution with mean 0 and variance σ.
A quadratic polynomial in days on test with fixed regressions for sex and batch, random regressions for additive genetic, pen, litter and individual permanent environmental effects was used, with two different models for the residual variance: constant in model 1 and modelled with a quadratic polynomial depending on the day on test d m as follows in model 2:.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com