SRMSR

AcronymDefinition
SRMSRStandardized Root Mean Square Residual
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The first factor explains 28.14% of the variance and the indexes of fit confirm that the data fits an essentially unidimensional structure (GFI = .96; SRMSR = 0.10).
A poor fit with the empirical variance-covariance matrix of the 50 items was found, [X.sup.2](V=251, df=1165)=4538.6, p<.001, chi-square/df ratio=3.90, Standardized Root Mean Square Residuals (SRMSR)=0.099, Bentler Comparative Fit Index (CFI)=0.582, Normed Fit Index=0.512.
The new set of items was not statistically significant at the item-fit test, thus fitting adequately the data, and the overall M2 fit indexes of the model were as follows: CFI = 0.98, TLI = 0.98, RMSEA = 0.04, and SRMSR = 0.05.
The absolute fit was good with a SRMSR of 0.035, and the fit was much better than a model with zero correlations since CFI = 0.888 (Table 2).
Satorra- Root Mean Bentler Square Error of Scaled Approximation Chi-Square (RMSEA) (90% CI) One-factor model [8, 9] 218.72 * 0.098 (0.086/0.11) 2nd-order factor model 1888.05 * 0.14 (0.13/0.14) Bifactor model 629.45 * 0.077 (0.071/0.083) Akaike Comparative Standardized Information Fit Index Root Mean Criterion (CFI) Square (AIC) Residual (SRMSR) One-factor model [8, 9] 254.72 0.89 0.060 2nd-order factor model 1976.05 0.81 0.14 Bifactor model 737.45 0.95 0.067 Degree of freedom One-factor model [8, 9] 27 2nd-order factor model 127 Bifactor model 117 * Significant for P < 0.001.
The fit of this three-factor model, [DELTA][chi square]2(4) = 171.10, p < .001, SRMSR = .13, GFI = .82, CFI = .72 was significantly worse than the fit of the four-factor model.
Single-sample CFAs indicated that a four-factor model fits well in both the student sample ([chi square] (98) = 246.58, p < 0.01; CFI = 0.97, TLI = 0.97, RMSEA = 0.049, SRMSR = 0.045) and in the employee sample ([chi square] (98) = 160.82, p < 0.01; CFI = 0.96, TLI = 0.95, RMSEA = 0.058, SRMSR = 0.068).
Goodness-of-fit of the CFA model was evaluated using multiple recommended indices of good-fit: the Comparative Fit Index (CFI), the Non-Normed Fit Index (NNFI), the Standardized Root Mean Squared Residuals (SRMSR) and Root Mean Square Error of Approximation (RMSEA).
The Standardized Root Mean Square Residual (SRMSR) is a measure of mean absolute correlation residual.
The goodness-of-fit indices we included and their guideline cut-off criteria (see Hu & Bentler, 1998, 1999) were: the standardized root mean square residual (SRMSR, [less than or equal to] .08), the root mean square error of approximation (RMSEA, [less than or equal to] .06), the Tucker-Lewis Index (TLI, [greater than or equal to] .95), the comparative fit index (CFI, [greater than or equal to] .95), and the Akaike information criterion for comparisons among non-nested models (AIC, where relatively smaller coefficients indicate better fit).
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