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For each brain region, standard errors are listed in parentheses and are expressed as the percentage of the variable itself.
Figure 4 illustrates the number of relevant variables that were selected from UVE-PLS-DA as a function of the percentage of the variable selection frequency.
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We illustrate the numerical results, obtained from the applied optimal control theory (i.e. Pontryagin's maximum principle), and we show the effect of the percentage of the awareness variable (control) on minimizing the number of susceptible and infected individuals and increasing the number of the removed ones.
However, the percentage of the response variable variation that is explained by the linear model or R value should be considered as it is only 8.7%.> -wrap-foot> Profortion of variance explained by the model.
An overall integration score was derived for each home based on the percentage of the six integration variables for which it had indicated integrated working with the local health service.
The variables were described by the mean and standard deviation for continuous variables with a normal distribution, the median and 25th 75th percentiles for nonnormally distributed continuous variables, and the percentage of the total for categorical variables.
For reporting purposes, we back transformed the data to demonstrate the percentage of the contribution of each variable to the cost value.
The optimal combination of attributes minimizes a weighted sum of total fractional misclassification and the percentage of the total number of variables employed to obtain the misclassification.
From this, effect ratios were computed that represent the percentage of the total effect of the independent variable on the dependent variable that is explained by the mediator (Shrout and Bolger, 2002).
The squared factor loadings indicate the percentage of the variance in the original variable that is explained by a factor.
The percentage of the presence of a given variable (for example age > 70 years) was represented using a local polynomial regression.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com