TABLE 2.
Model fit statistics.
| Fit indices | Cutoff criterion | Sensitive to N | Penalty for model complexity |
| Absolute fit indices | |||
| Chi-square (χ2) | Lowest comparative value between measurement models Significant (p > 0.01) | Yes | Yes |
| Approximate fit indices | |||
| Root-mean-square error of approximation (RMSEA) | <0.08 but >0.01 90% CI range does not include 0 | Yes | Yes |
| Standardized root mean square residual (SRMR) | <0.08 but >0.01 | Yes | No |
| Incremental fit indices | |||
| Comparative fit index (CFI) | >0.90 but <0.99 | No | Yes |
| Tucker–Lewis index (TLI) | >0.90 but <0.99 | No | Yes |
| Akaike information criterion (AIC) | Lowest value in comparative measurement models | No | No |
| Bayes information criterion (BIC) | Lowest value in comparative measurement models | No | No |
Adapted from Kline (2011) and Wang and Wang (2020).