One factor model reflected by the same 6 categorical items measured over 3 time intervals, each 3 months apart. Data arrange in Long Format. E.g.,
T1_B BY v1 v2 v3 v4 v5 v6; T2_B BY v7 v8 v9 v10 v11 v12; T3_B BY v13 v14 v15 v16 v17 v18;
!Time One Uniquenesses WITH Time Two & Three Uniquenesses v1 v2 v3 v4 v5 v6 WITH v7 v8 v9 v10 v11 v12; v1 v2 v3 v4 v5 v6 WITH v13 v14 v15 v16 v17 v18;
!Time Two Uniquenesses WITH Time Three Uniquenesses v7 v8 v9 v10 v11 v12 WITH v13 v14 v15 v16 v17 v18;
Hypothesis One: Correlated Uniquenesses become smaller over successively larger time intervals. That is, the size of the correlated uniqueness between Time 1 and Time 2 will be larger than those observed between Time 1 and Time 3 etc. Lets say that I expected the correlated uniquenesses to decrease in a quadratic fashion as one test; and then as a second test I expect them to halve in size each time. Note that I have more than 3 time waves.
Question 1. How might one impose such constraints?