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However, the model only explained 2% of the total deviance in the data.
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The model was able to explain 72% of the total deviance in herbivore density.
This final model included five predictors and explained 34% of the total deviance in woody cover change.
Our final models for the simplified set of 31 combined, 25 facilitator (Supplementary Fig. 6) and 12 driver (Supplementary Fig. 7) explanatory variables explained 78%, 75%and51%1% of the total deviance in woody cover change, respectively.
Hanski and Saccheri (2006) also identified heterozygosity (MLH) as having an important role within population dynamics, accounting for 26% of the total deviance in a model developed for population extinction events within fragmented Glanville fritillary butterfly (Melitaea cinxia) populations.
All three variables were highly significant (Anova: P < 0.001), but differed in influence; 18.5% of the total deviance was independently explained by family, while 0.5%and0.4%4% of the deviance was explained by exposure time and gender, respectively.
The model was fitted by minimising the total deviance.
This model parameter was best accounted for by the CG factor (9% of the total deviance).
Predictive deviance (expressed as a percentage of the total deviance) provides a measure of the goodness-of-fit between predicted and raw values.
The PD factor best accounted for Discrete time (31% of the total deviance) and Model specificity (18%).
The deviance differences will be summed across the test studies: the best-generalizing model was that with the lowest total deviance difference.
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CEO of Professional Science Editing for Scientists @ prosciediting.com