IBM® SPSS® Amos™ 28

In the case of positive definite covariance matrices, a determinant near zero indicates that at least one observed variable is nearly linearly dependent on the others. The consequences of this depend on the specified model and on the discrepancy function. From a numerical point of view, a determinant near zero may make it difficult to estimate the parameters of the model. From a statistical point of view, a determinant near zero may imply poor estimates of some parameters (which will show up as large estimated standard errors).

The determinant of the sample covariance matrix is displayed when

▪you display sample moments,

and

▪the sample sample covariance matrix is positive definite.