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The robustness check performed for Model II (see Table 9) also shows virtually no change in coefficients and p-values.
The overall predictive accuracy of model is tested on estimation and holdout sample to test whether change in coefficients (re-estimated) with recent data set improves the predictive accuracy of the model.
In fact, the change in coefficients is modest.
After adjustment for mediating variables, coefficients were largely reduced, particularly among boys, and the main predictor of change in coefficients was the inclusion of height in the models.
We found no confounding by medications, sex, or myocardial infarction history because the change in coefficients after adding these variables was < 10%.
Identification of any influential points prompted refitting the model using conditional logistic regression, omitting influential points and assessing the change in coefficients and their statistical significance.
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Thus, additional sensitivity analysis was needed to verify the changes in the ESV for a given change in coefficient.
From the Figure 7, it is understood that the ranking of supplier is highly sensitive with the change in coefficient.
Our measures of sensitivity included change in coefficient values, prediction success, and the area of mapped habitats following the systematic introduction of geographic error and bias in occurrence data, thematic misclassification of resource maps, and variation in model design.
The results, as reported in Table 7, indicate that CS values in all studied periods were below 1, which means that the estimated overall ecosystem value (ESV) was considered to be inelastic (low sensitive) to the change in coefficient values.
% change in coefficient compares adjusted models before and after additional adjustment for nitrogen dioxide.
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