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The χ2 test, NFI, NNFI, CFI, RMSEA, GFI, and AGFI have been applied to the evaluated model finesses (Jöreskog and Sörbom 1993).
We evaluated model results at 250, 500 and 1000-m spatial resolutions, and found that results are insensitive to spatial resolution.
We evaluated model performance based on root mean square error (RMSE) and RMSE as a percent of the mean of the field inventory TLB (%RMSE), and absolute bias (Eqs. 5, 6, 7) and residual diagnostics.
This approach gives the same generalizability as a simultaneously fitted model but has the advantages of an evaluated model fit separately for the lower order and the higher order levels.
We evaluated model performance with parameters informed by four approaches: 1) expert opinion; 2) sensitivity analysis; 3) sensitivity analysis informed model optimization; and, 4) simulated annealing (uninformed) model optimization.
We conducted 46 weeks of avian surveys (between 14 February 2005 and 17 February 2006) and evaluated model fit of 6 a priori models relative to pond use by an avian group via Kullback Leibler information.
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After two measurements are taken, integral-based parameter fitting [60] is used to identify a clinically evaluated model-based insulin sensitivity [34 36].
Instead, we evaluated models based on the other fit indices.
Table 7 shows a summary of the ten evaluated models with all their data ranges.
We evaluated models' discrimination using the area under the receiver operating characteristic curve (AUROC).
Finally, the authors evaluated models for predicting the percentage of foreign population.
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