As a whole, the ICD 9 diagnoses model explained up to 17.1% (R2 Nagelkerk value) of the variance [ 57, 58] in the dependent variable.
As a whole, the ACS model explained up to 12.3% (Nagelkerk R2 value [ 57]) of the variance of the dependent variable.
The overall daytime and nighttime UHI models explain up to 77 and 90percentt of UHI variation, respectively.
Nevertheless, the fact that independent variables in the mediation models explain up to 57% of variability in students' enjoyment again points to satisfactory model fit.
The MLR and PLS models explained up to 73%and70%0% of the Kd (Am) variability, respectively; thus, they can be used to estimate Kd (Am) values directly from soil properties.
Random forest modeling explained up to 63% of the Rim fire burn variance using seven predictors: time since previous fire, actual evapotranspiration (AET), climatic water deficit (Deficit), previous maximum burn severity, burning index, slope position, and solar radiation.
Starting with the robustness of the results, Wald Chi Square results in Table 3 for both total peak demand and domestic peak demand regressions are robust and the models explain up to 79%% (Adjusted R2) of relationships between the total peak demand and the explanatory variables.
Starting with the robustness of the results, Wald chi2 results in Table 7 for both regressions 1 and regression 2 are robust and the models explain up to 78%% (adjusted R 2) of relationships between the total peak demand and the explanatory variables.
The clinical models explained up to 39percentt of the variance in local peak pressures.
