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In such circumstances, the global criteria method works toward finding an agreement between all objectives, so that it minimizes the total relative deviance of all objectives from its optimal values (z i *).
Relative deviance reduction of best single variable model is indicated by dashed horizontal line (associated with Figure 7C, E, respectively).
Relative deviance reduction and linear filter values for prediction of female song (A and B ) or male song (C and D ).
Model performance (indicated by relative deviance reduction) reveals the behaviors most predictive of female song (C ) and male song (E ) (see 'Materials and methods').
Model performance (relative deviance reduction) was evaluated using cross-validation; that is, model parameters were fitted from 80% of the data, and the model was tested with the remaining 20% of the data (random subsampling).
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The model was also checked for outliers using plots of Pearson's residuals and the deviance residuals (which measure the relative deviation between the observed count data and estimated count data) against observation number.
The analyses were done in R, using the generalized linear model function to compute relative risks and deviances, and the vcovHC function of the sandwich package was used to compute robust standard error estimates for the relative risk estimates.
Model 2 found that shark sex (LRT12 = 35.893, p = 0.0003) had only a small effect (mean deviance ∼1) relative to patch effect (Table 3).
To evaluate whether the addition of random effects for these two parameters resulted in a better fitting model, the change in the deviance statistics relative to the baseline model was used.
Our results showed that the stochasticity of the simulations did not have a major influence on the predicted HZ incidences per parameter set as illustrated by the fact that the median relative variance of the deviance of the top 13 parameter sets for the three runs is only 1.9% (also see Figure 2 figure supplement 2).
For men, the transformed model significantly improved model fit relative to the untransformed model (Deviance Difference = 231.79, p-value < 0.001), the linear-quadratic model (Deviance Difference = 105.62, p-value < 0.001) and the categorical model (Deviance Difference = 81.63, p-value < 0.001).
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com