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A significant increase in the amount of variations explained by the sub-scale scores as compared to the overall FACT-G score was observed (increase in the proportion of the total variance explained from adjusted R = 0.508 to 0.628).
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Permutational multivariate analysis of variance (Adonis) tests were performed on weighted UniFrac values to determine the amount of variation explained by soil chemistry.
The differences in the amount of variation explained by the spatial variables in both attributes (cover and diversity) indicate their different spatial arrangement at the scale which we considered.
However, the amount of variation explained by even our best models was quite low, suggesting that NDVI habitat models may not presently be an accurate tool for extensive modeling of avian communities.
(8 and 9), but slightly less than the amount of variation explained by the log-linear models given by Eqs.
The additional amount of variation explained by the models when relative height terms were included is based on predicted values of relative height rather than measured values.
The adjusted R2 calculates the amount of variation explained by the form after adjusting to the number of parameters in it.
Once the model with the lowest BIC was chosen for each circular area the amount of variation explained was graphed relative to each other sample size (Figure 5b).
This was greater than the amount of variation explained by the addition of height terms to the nonlinear models given by Eqs.
We used PerMANOVA (implemented in the R-vegan function adonis) to distinguish the amount of variation explained by the sample fraction, the domestication status (wild or cultivated) or the interaction between these factors.
Including taxonomic group as a covariate increased the amount of variation explained to 91% and revealed statistically significant differences in slopes and intercepts among groups (Table 1).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com