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R2 is a measure of explained variance.
cR= squared correlation coefficient in order to obtain a measure of explained variance.
To assess model discrimination, we use the R statistic as a measure of explained variation.
For the measure of explained variance, all analyses showed significant reduction from L-Healthy to the other two masks.
This percentage change can be taken as a measure of explained SES effect by other risk factors.
Model performance was estimated with the Nagelkerke Pseudo- R2 statistic (a measure of explained variation in the model).
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Additional file 2: Measures of explained variation.
We use two measures of explained variation appropriate for binary outcome - direct and indirect [ 16].
These include measures of explained variation, which quantify the proportion of variation in the outcome that can be explained by the predictors in the model.
Measures of explained variation (R) for fixed effects is used to assess the contribution of covariates on the longitudinal measures of CVD risk and components (30).
The addition of neuropsychological and heart rate measures increased the amount of explained variance to 28.4%.
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