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The model adequacy is verified by the confirmation tests.
The determination of model adequacy is made on the basis of goodness of fit statistics; however, several models all with different parameter values may pass these statistical tests.
The model adequacy is summarized by p-values that indicate whether the model is an accurate reflection of the data.
A simple test for the model adequacy is to compare the overall (Kaplan Meier) survival curve to the model-based predicted survival and, ideally, for any group of patients the two should be close, if not identical.
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The model adequacy was very satisfactory as the coefficient of determination was 0.94.
Good first- and second-order model adequacy was found for pesticide calibration.
Diagnostics of model adequacy was performed by predicted versus actual, normal % probability and internally studentized residuals.
The model adequacy was experimentally validated in triplicate at optimized levels of factors (Bagewadi et al. 2016a).
The model adequacy was also verified through additional bleaching experiment within the fixed parameters ranges, and was discussed.
The model adequacy was tested by contrasting a simulated sample against an independent sample of real animals.
This method was efficient; only 20 experiments were necessary to assess these conditions and model adequacy was very satisfactory, as the coefficient of determination was 0.9560.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com