The Multiple-Group Analysis window is used to fit a model simultaneously to multiple groups. Cross-group constraints are automatically created in a way consistent with the recommendations of Bollen (1989a), Byrne (2016), Kline (2016) and others.
When you have data from multiple groups, you often start by asking if it is necessary to draw a separate path diagram for each group, or if the same path diagram will do for all groups. If you conclude that all the groups share the same path diagram, you can proceed to ask whether parameter values are invariant across groups. For example, if you are studying boys and girls, you might want to know whether boys and girls have the same regression weights, or if only certain regression weights are the same for boys and girls. Of course there are also variances and covariances as well as regression weights to consider. Because of the large number of possible cross-group constraints, it is necessary to have a strategy for deciding which cross-group constraints are worth testing and in what order to test them. Bollen (1989), Kline (1998), and others discuss such strategies. Amos implements an automatic procedure for generating a nested hierarchy of models in which cross-group constraints are introduced incrementally in a pre-chosen order.
No automatic procedure can anticipate the purpose of every individual study. If necessary, you can modify Amos's automatically generated cross-group constraints to suit the needs of an individual study. However, no such customization will be necessary in most cases. You also have the option of performing multiple-group analyses by imposing cross-group constraints manually.
See Examples 24 and 25 in the User's Guide for a tutorial on performing multiple-group analyses with automatically generated cross-group constraints.