Sentence examples for model fitting index from inspiring English sources

To measure how well a network satisfies a scale-free topology, we use the fitting index proposed by Zhang & Horvath [30], i.e., the model fitting index R2 of the linear model that regresses log(p k)) on log(k) where k is connectivity and p(k) is the frequency distribution of connectivity.

To measure how well a network satisfies a scale-free topology, we use the fitting index proposed by Zhang & Horvath [ 71] (i.e., the model fitting index R 2 of the linear model that regresses log(p k)) on log(k) where k is connectivity and p(k) is the frequency distribution of connectivity).

The threshold r value 0.80 (for hESCs) or 0.90 (for mESCs) that we chose corresponded to the linear regression model fitting index R2 value 0.84 or above, which suggests scale-free topology of the resulting network.

The linear regression model fitting index R^2 can be used to quantify how well a network satisfies a scale-free topology.

The threshold of 0.93 was selected such that it gave the best overall fit to each dataset based on the criteria such as the scale-free topology model fitting index, mean network connectivity, and network density.

To quantify the fit to the scale free topology model or to the truncated exponential model, we used the model fitting index R-squared of the corresponding linear model involving the log transformed variables [ 16].

Model fit indices like CFA's and RMSEA showed good fit, for both types of content, and predictive and discriminant validity was assessed.

As a result of analysis of the model, fit indices were examined (NFI = 0.91, CFI = 0.93, RMR = 0.073).

These models fit indices are in Table 3.

Table 9 Model fit indices information Model Fit index Conceptual model Recommended criterion Judgment SERVQUAL χ2 2004.84 (p = 0.000) – – χ2/d.f.f

When sampling weights are applied, LISREL 8.80 only provides RMSEA for the model fit index.