Criteria for indices in SEM modeling
| Index | Threshold for good fit | Brief description | |
|---|---|---|---|
| Chi-squared | x2 | Not significant (p > 0.05) or low in relation to degrees of freedom | Evaluates the overall adequacy of the model. Sensitive to sample size |
| Normed fit index | NFI | >0.90 | Compare the proposed model with a null model with no relationships |
| Tucker-Lewis index | TLI/NNFI | >0.90 | Adjust the model for complexity and improve if the reduction in χ2 is proportional to the increase in degrees of freedom |
| Comparative fit index | CFI | >0.90 | Compares observed and predicted covariance matrices |
| Root mean square error of approximation | RMSEA | <0.05 (good); <0.08 (acceptable) | Evaluates the mean error per degree of freedom; includes confidence interval |
| Standardized root mean square residual | SRMR | <0.05 | Indicates the standardized average discrepancy between the observed and modeled covariance matrices |
| Index | Threshold for good fit | Brief description | |
|---|---|---|---|
| Chi-squared | x2 | Not significant ( | Evaluates the overall adequacy of the model. Sensitive to sample size |
| Normed fit index | NFI | >0.90 | Compare the proposed model with a null model with no relationships |
| Tucker-Lewis index | TLI/NNFI | >0.90 | Adjust the model for complexity and improve if the reduction in |
| Comparative fit index | CFI | >0.90 | Compares observed and predicted covariance matrices |
| Root mean square error of approximation | RMSEA | <0.05 (good); <0.08 (acceptable) | Evaluates the mean error per degree of freedom; includes confidence interval |
| Standardized root mean square residual | SRMR | <0.05 | Indicates the standardized average discrepancy between the observed and modeled covariance matrices |
Sharing content requires targeting cookies to be enabled. Please update your cookie preferences to use this feature.