Dear Professor, I’m running a longitudinal design with two latent constructs: “IG” and “IS”. I have two measurement points T1 and T2 (IG_T1,IG_T2 and IS_T1, IS_T2) and the hypothesis is that IG_T1 predicts IS_T2 (even when controlled for IS_T1) and that IS_T2 itself is predictive of IG_T2. The syntax is as follows:
IG_T2 on IS_T1 IS_T2 IG_T1; IS_T2 on IG_T1 IS_T1;
The problem is that I get a very unexpected negative path between IG_T2 and IS_T1, even though the path between IS_T2 and IG_T2, the path between IS_T1 and IS_T2 and the path between IG_T1 and IS_T2 are positive. There’s no logical reason why IS_T1 should have a different effect than IS_T2 and I wonder whether it is correct to account for the effect of IG_T2 on IS_T1 when the same construct at the second measurement point (IS_T2) is part of the equation. I would appreciate any help. Thank you very much.
The correlation between IG and IS at T1 is about .65 and the correlation between the two slope factors is almost the same. If this is a problem of multicollinearity, would it be rational to exclude the paths between IG_T2 and IS_T1 when the equation accounts for IS_T2? Thank you very much for your help.