Since JMP emphasizes visualization, the augmented factor correlation matrix with color coding will be a useful piece of information in the SEM platform. The factor correlation matrix is a useful for researchers during scale construction. For multi-item constructs scale builders look for convergent and discriminant validity. This piece of information can be obtained easily since JMP 15 can now compute factor scores for latent variables. This correlation matrix can be augmented as follows:
1. Correlation values on the lower diagonal
2. Correlation-squared values reflecting shared variance between factors on the upper diagonal
3. Average Variance Extracted (AVE) which is the variance each factor shares with its own indicators on the diagonals. This can also be thought of as the average communality of the construct.
Here is an example:
For convergent validity, we want AVE > 0.5 indicating the construct explains > 50% of the variance of its indicators
For discriminant validity, we want the diagonal values to be higher than values to the right or above since this establishes that the factor shares more variance with its own indicators than other factors. When such is not the case, color coding the violations will be more useful.