HI Littleriver,

there are some issues here and a neat solution. First, If you compute the interaction yourself as a new variable (`agegp*SR`) you are forcing the model to be estimated with the independent variables with two different scales. One is the scale the software gives by default (centered continuous variables and centered coding for the categorical ones) and the other is the scale used to compute the interaction term (in your case, centered continuous and dummy for categorical). So the model is a hybrid and the results are inconsistent. If you want to have a consistent model (but please see later on a better solution) you should code your cat variable as dummy. But even by doing that, you would not get the plot you're expecting, because the software does not know how to condition the independent variables to compute the simple effects required for the plot.

The solution is to specify the interaction within the module. Simply go to "Fixed Effects", select both terms you want to interact and push the button to move the interaction term in the "Model Terms".

If you do that, you get the right estimates for the plots.

To be sure, I've checked the results with the proposed solution in GAMLj and SPSS, and they converge.

P.S: look up the new version 1.5.0 of GAMLj, with lots of improvements. The old .omv files may give an error with the new version. In case of error, please be sure all the options in the UI have a selected value, and everything will be fine.