Sentences with phrase «fit indices indicated»

Root mean square error of approximation and other fit indices indicated psychoFmetric properties for both versions to be acceptable.

Overall, the fit indices indicate that the model displayed an adequate fit for the sample (Bentler, 1990).

Not exact matches

Results indicated that both high - quality close friendships and a drive to fit in with peers in adolescence were associated with better health at age 27, even after taking other potentially influential variables such as household income, body mass index, and drug use into account.

The above historical performance figures from Morningstar indicate that the fund had a higher volatility (expressed as a standard deviation of returns) and underperformed the S&P 500 ® index, its best - fit benchmark, on a risk - adjusted basis (Sharpe Ratio) in both the three - and five - year trailing periods.

Further, the comparative fit index (CFI) and the incremental fit index (IFI) were measured, and values equal to or higher than 0.9 for these indices indicate an acceptable fit to the model.

A close fit to the model is indicated by values less than 0.05, according to the root mean square error of approximation (RMSEA) fit index (Browne & Cudeck, 1993).

In particular, confirmatory factor analysis indicated satisfactory fit indices (CFI: 0.98, SRMR: 0.05), and internal consistency of the scale (α = 0.87).

The global fit indices included: The X2 - degrees of freedom (d. f) ratio < 2.0, RMSEA < 0:06, CFI > 0:90, NFI > 0:90, GFI > 0.85, AGFI > 0.85 indicated an acceptable fit.

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.

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.

Following the a priori tests, we considered relaxing the equality constraints on the relations of other wave 1 predictors with both latent constructs, starting with the predictor that resulted in the greatest improvement of fit provided the modification index indicated the improvement was significant at a more stringent p level of.001 or less.

At ages 1.5 and 3 the BIC and the BLRT indicated that five profiles resulted in better model fit than four profiles (fit indices are reported in Supplementary Table S1).

Confirmatory factor analyses indicated that while the hypothesized three - factor model fit significantly better than an alternative one - factor model, the fit indices associated with the three - factor model were below satisfactory cutoffs, thus tempering conclusions that the best fitting structure was found and highlighting the need for additional research.

Fit indices obtained through Confirmatory Factor Analysis indicated that the six - factor structure of the DERS fit the data adequately and that most items loaded strongly on their respective latent factFit indices obtained through Confirmatory Factor Analysis indicated that the six - factor structure of the DERS fit the data adequately and that most items loaded strongly on their respective latent factfit the data adequately and that most items loaded strongly on their respective latent factor.