IBM® SPSS® Amos™ 28

When the data contain missing values, the Saturated option affects whether the saturated model is fitted. If Saturated is checked, the saturated model will be fitted. With complete data, the saturated model is always fitted.

With incomplete data, the null models (Null 1, Null 2, Null 3 and Null 4) are fitted only when the saturated model is fitted.

For maximum likelihood (Ml), generalized least squares (Gls) and asymptotically distribution-free (Adf) estimation, fitting the saturated model is necessary for calculating the chi square statistic and all of the fit measures that depend on the chi square statistics.

With incomplete data, it is not practical to fit the saturated model if the number of observed variables is very large. For this reason, the specification search routine does not fit the saturated model or any of the null models if the number of observed variables exceeds 20 and the data contain missing values.