IBM® SPSS® Amos™ 28

With one exception, Amos assumes that the exogenous variables in a model are correlated, and it estimates the covariance between every pair of exogenous variables. The exception to this default assumption concerns unique variables — exogenous variables that are unobserved and have a direct effect on only one variable. Amos assumes that unique variables are uncorrelated with each other, and with every other exogenous variable in the model.

You may explicitly permit two variables to be correlated by using the string, <>, as illustrated in the following example:

    Dim Sem as New AmosEngine
    . . .
    Sem.AStructure("variable2 <> variable3")

where Amos is told that variable2 and variable3 may be correlated, and is asked to estimate their covariance.

Since the AStructure method ignores dashes, the following three lines are equivalent:

    Sem.AStructure("variable2<>variable3")
    Sem.AStructure("variable2 <---> variable3")
    Sem.AStructure("variable2 <----------> variable3")

You can place constraints on the covariances of exogenous variables, as in the following example:

    Dim Sem as New AmosEngine
    . . .
    Sem.AStructure("variable1 <---> variable2 (alpha)")
    Sem.AStructure("variable2 <---> variable3 (alpha)")
    Sem.AStructure("variable3 <---> variable4 (alpha)")
    Sem.AStructure("variable1 <---> variable3 (beta)")
    Sem.AStructure("variable2 <---> variable4 (beta)")
    Sem.AStructure("variable1 <---> variable2 (0)")
    . . .

In this example, the first three covariances listed are required to be equal because they are all labeled alpha. Similarly, the two covariances labeled beta are required to be equal to each other. variable1 and variable2 are declared to be uncorrelated, so that Amos will not attempt to estimate their covariance. (It is also possible to fix a covariance to a nonzero value, although reasons for doing so are rare.)