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The quality difference is also underlined by the values for sensitivity from Table 3.
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Depending on the study done and combination of tests and reference standard thresholds applied, they range from 18%to98%8% for sensitivity and from 17% to 99% for specificity [ 66].
The predictive values of the Risk Factor Model across all six academic years for sensitivity ranged from 75% - 85%; specificity ranged from 73% - 90%; PVP ranged from 85-93%; and PVN resulted in a range of 62% - 78%.
The robustness of the results were analyzed using the methods for sensitivity analysis from DEFINITE toolbox, based on frequency tables from 10,000 simulations run after introducing uncertainty ranges in input values and assigned weights (Janssen and van Herwijnen 1994).
In the most sensitive algorithm (that using five diagnostic codes), estimates for Sensitivity ranged from 14.5%CI9595% 10.3-19.6) to 45.7% (CI95% 41.4-50.1).
This paper is an attempt to seek a relatively unified model for sensitivity analysis from three aspects: hydraulic parameters (turbine flow and turbine head), mechanic parameters (axis coordinates and axial misalignment) and electric parameters (generator speed and excitation current).
Median values for sensitivity ranged from 0.37 – 0.37.
The estimates for sensitivity resulting from this study varied between 20 and 50%, while specificity was between 92 and 100%.
One-Way ANOVA with Bonferroni's post hoc test reveals that half-maximal value for sensitivity differs from all the other parameters (p < 0.05, n = 5).
For γ > 0.2, however, there was little benefit from imputation, with very few opportunities for higher sensitivity from (CC) to (MI*): most values for the differential in − log 10 (p ) are actually negative.
Marvel, K. et al. Implications for climate sensitivity from the response to individual forcings.
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