Sentences with phrase «goodness of fit index»

The global model fit to the data was tested by Chi - square, Root Mean Square Error of Approximation (RMSEA), Comparative Fit Index (CFI) and Goodness of Fit Index (GFI).

The findings of CFA were assessed on the basis of several goodness - of - fit statistics such as goodness of fit index (GFI), comparative fit index (CFI), standardized root mean square residual (SRMR) and root mean square error of approximation (RMSEA).

Another criterion of goodness of fit index (GFI) is employed which determine the discrepancies between the assumed model and the observed covariance matrix.

The most commonly used goodness - of - fit statistics were used in the present study (Byrne, 2016; Laveault & Grégoire, 2014), that is, the chi - square to its degrees of freedom (χ 2 / df; a χ 2 / df close to or less than 2.0 was considered to be indicative of a good model fit, and close to or less than 5.0 as indicative of a satisfying fit); the Root Mean Square Error of Approximation (RMSEA; good fit < 0.05, satisfying fit < 0.08); the Standardized Root Mean Square Residual (SRMR; good fit < 0.05, satisfying fit < 0.08); the Comparative Fit Index (CFI; good fit ≥ 0.95; satisfying fit ≥ 0.90), and the adjusted goodness of fit index (AGFI; good fit ≥ 0.95; satisfying fit ≥ 0.90)(Hu & Bentler, 1999).

We analyzed data using the LISREL 8.80 analysis of covariance structure approach to path analysis and maximum likelihood estimates.42 We used four goodness - of - fit statistics to assess the fit of our path model with the data: the Root Mean Square Error of Approximation test (RMSEA), the Norm - fit index (NFI), the adjusted Goodness of Fit index (GFI) and the mean Root Mean Square Residual (RMR).

All goodness of fit indices suggested an excellent fit between the models and the data (Table I, models five and six).

Not exact matches

Goodness - of - fit indices for the six - factor model with 14 items indicate a well - adjusted fit to the data (χ2 / df = 1.427, RMSEA = 0.019, SRMR = 0.021, CFI = 0.992, AGFI = 0.982) which confirms study 1's findings.

Goodness of fit was evaluated by the Standardized Root Mean Square Residual (SRMR), the Root Mean Square Error of Approximation (RMSEA, 90 % CI), the Comparative Fit Index (CFI), and finally by the Tucker - Lewis index (TLfit was evaluated by the Standardized Root Mean Square Residual (SRMR), the Root Mean Square Error of Approximation (RMSEA, 90 % CI), the Comparative Fit Index (CFI), and finally by the Tucker - Lewis index (TLFit Index (CFI), and finally by the Tucker - Lewis index (Index (CFI), and finally by the Tucker - Lewis index (index (TLI).

Fit indices used to evaluate the model included a χ2 goodness - of - fit test (nonsignificant values indicate good fits), the comparative fit index (scores of > 0.95 indicate better fits), the root mean square error of approximation (values of < 0.05 indicate good fits), and the standardized root mean square residual (values of < 0.08 indicate good fits).43, 44 Missing values were imputed through multiple imputation by using functions in the missing data library in S - Plus (Insightful Corp, Seattle, WA).45, 46 The combined data for the cross - lagged / survival model converged more quickly with 15 imputed data sets than did the model that used a likelihood - based approach to missing daFit indices used to evaluate the model included a χ2 goodness - of - fit test (nonsignificant values indicate good fits), the comparative fit index (scores of > 0.95 indicate better fits), the root mean square error of approximation (values of < 0.05 indicate good fits), and the standardized root mean square residual (values of < 0.08 indicate good fits).43, 44 Missing values were imputed through multiple imputation by using functions in the missing data library in S - Plus (Insightful Corp, Seattle, WA).45, 46 The combined data for the cross - lagged / survival model converged more quickly with 15 imputed data sets than did the model that used a likelihood - based approach to missing dafit test (nonsignificant values indicate good fits), the comparative fit index (scores of > 0.95 indicate better fits), the root mean square error of approximation (values of < 0.05 indicate good fits), and the standardized root mean square residual (values of < 0.08 indicate good fits).43, 44 Missing values were imputed through multiple imputation by using functions in the missing data library in S - Plus (Insightful Corp, Seattle, WA).45, 46 The combined data for the cross - lagged / survival model converged more quickly with 15 imputed data sets than did the model that used a likelihood - based approach to missing dafit index (scores of > 0.95 indicate better fits), the root mean square error of approximation (values of < 0.05 indicate good fits), and the standardized root mean square residual (values of < 0.08 indicate good fits).43, 44 Missing values were imputed through multiple imputation by using functions in the missing data library in S - Plus (Insightful Corp, Seattle, WA).45, 46 The combined data for the cross - lagged / survival model converged more quickly with 15 imputed data sets than did the model that used a likelihood - based approach to missing data.

Results: The global justice model with autocorrelations had the most satisfactory goodness - of - fit indices.

GFI = Goodness - of - Fit Index; CFI = Comparative Fit Index; RMSEA = Root Mean Square Error of approximation.

Other criteria of Goodness of - fit index (GFI) was used which represented the latent factors.

Goodness - of - fit was assessed by evaluating the Satorra - Bentler scaled chi - square, the Comparative Fit Index (CFI), the Root Mean Square Error of Approximation (RMSEA), and the Standardized Root Mean Square Residual (SRMfit was assessed by evaluating the Satorra - Bentler scaled chi - square, the Comparative Fit Index (CFI), the Root Mean Square Error of Approximation (RMSEA), and the Standardized Root Mean Square Residual (SRMFit Index (CFI), the Root Mean Square Error of Approximation (RMSEA), and the Standardized Root Mean Square Residual (SRMR).

Factor loading and goodness - of - fit indexes of one - factor model for the 10 - items CD - RISC factor structure.

The goodness of fit of the model was assessed using chi - square and the p - value, the Comparative Fit Index (CFI: Bentler 1989), and the Root Mean Square Error of Approximation (RMSEA: Steiger 199fit of the model was assessed using chi - square and the p - value, the Comparative Fit Index (CFI: Bentler 1989), and the Root Mean Square Error of Approximation (RMSEA: Steiger 199Fit Index (CFI: Bentler 1989), and the Root Mean Square Error of Approximation (RMSEA: Steiger 1990).