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We examined the influence of human disturbance on channel width using several indices of local and basinwide disturbance.
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We investigated the soil-geoform units in the Jarama–Henares interfluve and the Henares river valley using several indices to quantify and understand the evolution of soil and landscape patterns of the area during the Plio-Quaternary.
We tested goodness of model fit using several indices (see Supplemental Material, Table S1).
This study also used several indices to evaluate overall model fitness, including the χ test of absolute fit (p > 0.05), test of relative fit by the goodness-of-fit index (GFI > 0.90), the adjusted goodness-of-fit index (AGFI > 0.90), the Tucker Lewis index (TLI > 0.95), the comparative fit index (CFI > 0.90), and the root mean square error of approximation (RMSEA < 0.05).
The overall model fit was tested using several indices.
This study also used several indices, including Chi-square ratio (< 3), goodness of fit index (GFI>.9), adjusted goodness of fit index (AGFI>.8), normal fit index (NFI>.9) and root mean square of standardized residual (RMSR<.08) to evaluate overall model fitness [ 58].
To assess model fit, we used several indices: the comparative fit index (CFI), the Tucker-Lewis index, the root-mean-square error of approximation (RMSEA), and the standardized root-mean-square residual (SRMR; Hu and Bentler, 1999).
We used several indexes such as the Goodness of Fit Index (GFI), which should be greater than 0.90 for good-fitting models, GFI Adjusted for Degrees of Freedom (AGFI), with a value of 0.90 as the cut-off value [ 32] and Root Mean Square Residual (RMR), the larger the RMR value the less is the fit between the model and the data [ 30].
Presented next are the prediction accuracies of the models which were then evaluated using several statistical indices, such as the coefficient of determination (R 2) and root mean square error (RMSE).
Implied cause-and-effect relationships documented as 'rules' are evaluated by using several well-known indices of likelihood, including support, confidence, and lift [ 15].
The literature was unclear as to which elements of deprivation might be associated with Hgb A1c levels; we therefore used several validated indices of deprivation (income, material, social, combined).
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